The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Long‐term declines and recovery of meadow area across the world’s seagrass bioregions
Open accessAbstract
As human impacts increase in coastal regions, there is concern that critical habitats that provide the foundation of entire ecosystems are in decline. Seagrass meadows face growing threats such as poor water quality and coastal development. To determine the status of seagrass meadows over time, we reconstructed time series of meadow area from 175 studies that surveyed 547 sites around the world. We found an overall trajectory of decline in all seven bioregions with a global net loss of 5602 km 2 (19.1% of surveyed meadow area) occurring since 1880. Declines have typically been non‐linear, with rapid and historical losses observed in several bioregions. The greatest net losses of area occurred in four bioregions (Tropical Atlantic, Temperate North Atlantic East, Temperate Southern Oceans and Tropical Indo‐Pacific), with declining trends being the slowest and most consistent in the latter two bioregions. In some bioregions, trends have recently stabilised or reversed. Losses, however, still outweigh gains. Despite consistent global declines, meadows show high variability in trajectories, within and across bioregions, highlighting the importance of local context. Studies identified 12 different drivers of meadow area change, with coastal development and water quality as the most commonly cited. Overall, however, attributions were primarily descriptive and only 10% of studies used inferential attributions. Although ours is the most comprehensive dataset to date, it still represents only one‐tenth of known global seagrass extent, with conspicuous historical and geographic biases in sampling. It therefore remains unclear whether the bioregional patterns of change documented here reflect changes in the world's unmonitored seagrass meadows. The variability in seagrass meadow trajectories, and the attribution of change to numerous drivers, suggest we urgently need to improve understanding of the causes of seagrass meadow loss if we are to improve local‐scale management.
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
The file drawer problem and tolerance for null results.
Rosenthal, R. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.3.638 · Cited by 9,068 · cited 1×
“…the effects of specific disturbances or management actions; meadows could have disappeared before monitoring started; or published data can be subject to the ‘file- drawer’ problem (Csada et al., 1996; Rosenthal, 1979), meaning that sites with no change could be under- represented in our dataset.”
BackgroundA global crisis for seagrass ecosystems
ORTH, R. J., CARRUTHERS, T. J. B., DENNISON, W. C., DUARTE, C. M., FOURQUREAN, J. W., HECK, K. L., HUGHES, A. R., KENDRICK, G. A., KENWORTHY, W. J., OLYARNIK, S., et al. (2006) · BioScience · doi:10.1641/0006-3568(2006)56[987:agcfse]2.0.co;2 · Cited by 3,100
Estimating local biodiversity change: a critique of papers claiming no net loss of local diversity
Gonzalez, A., Cardinale, B. J., Allington, G. R. H., Byrnes, J., Arthur Endsley, K., Brown, D. G., Hooper, D. U., Isbell, F., O'Connor, M. I., & Loreau, M. (2016) · Ecology · doi:10.1890/15-1759.1 · Cited by 354
Breininger, D. R., Breininger, R. D., & Hall, C. R. (2017) · Conservation Biology · doi:10.1111/cobi.12791 · Cited by 16
Cited by
Arnull, J., Hashim, A. S., Ziyadh, A. M., Carter, A. L., Moosa, H., Wilson, A. M. W., Ganeshram, R. S., & Tudhope, A. W. (2025) · Marine Environmental Research · doi:10.1016/j.marenvres.2025.107228 · Cited by 6
Metadata
- Authors
- Dunic, J. C., Brown, C. J., Connolly, R. M., Turschwell, M. P., & Côté, I. M.
- Venue
- Global Change Biology
- Publisher
- Wiley
- Published
- 2021-06-20
- Volume
- 27
- Issue
- 17
- Pages
- 4096-4109
- ISSN
- 1354-1013 (ISSN-L)
- 1365-2486
- OpenAlex
- W3163862021
- Cited by
- 499
- References
- 4
- FWCI
- 30.88
- Type
- journal article
- Language
- en
- Open access
- hybrid
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
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.