The DOI matches its Crossref record; 56 of the 56 references it cites were found in a registry or an index.
Estimated migration rates under scenarios of global climate change
Abstract
Aim: Greenhouse‐induced warming and resulting shifts in climatic zones may exceed the migration capabilities of some species. We used fourteen combinations of General Circulation Models (GCMs) and Global Vegetation Models (GVMs) to investigate possible migration rates required under CO 2‐doubled climatic forcing. Location: Global. Methods: Migration distances were calculated between grid cells of future biome type x and nearest same‐biome‐type cells in the current climate. In `base‐case' calculations, we assumed that 2 × CO 2 climate forcing would occur in 100 years, we used ten biome types and we measured migration distances as straight‐line distances ignoring water barriers and human development. In sensitivity analyses, we investigated different time periods of 2 × CO 2 climate forcing, more narrowly defined biomes and barriers because of water bodies and human development. Results: In the base‐case calculations, average migration rates varied significantly according to the GVM used (BIOME3 vs. MAPSS), the age of the GCM (older‐ vs. newer‐generation GCMs), and whether or not GCMs included sulphate cooling or CO 2 fertilization effects. However, high migration rates (≥ 1000 m year−1) were relatively common in all models, consisting on average of 17% grid cells for BIOME3 and 21% for MAPSS. Migration rates were much higher in boreal and temperate biomes than in tropical biomes. Doubling of the time period of 2 × CO 2 forcing reduced these areas of high migration rates to c. 12% of grid cells for both BIOME3 and MAPSS. However, to obtain migration rates in the Boreal biome that were similar in magnitude to those observed for spruce when it followed the retreating North American Glacier, a radical increase in the period of warming was required, from 100 to >1000 years. A reduction in biome area by an order of magnitude increased migration rates by one to three orders of magnitude, depending on the GVM. Large water bodies and human development had regionally important effects in increasing migration rates. Main conclusions: In conclusion, evidence from coupled GCMs and GVMs suggests that global warming may require migration rates much faster than those observed during post‐glacial times and hence has the potential to reduce biodiversity by selecting for highly mobile and opportunistic species. Several poorly understood factors that are expected to influence the magnitude of any such reduction are discussed, including intrinsic migrational capabilities, barriers to migration, the role of outlier populations in increasing migration rates, the role of climate in setting range limits and variation in species range sizes.
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
Climate Change 1995: The Science of Climate Change
Houghton, J. T., Filho, L. G. M., Callander, B. A., Harris, N. L., Kattenberg, A., & Maskell, K. (1996) · Medical Entomology and Zoology · Cited by 3,503
Climate Change: The IPCC Scientific Assessment.
Bongaarts], [. (1992) · Population and Development Review · doi:10.2307/1971875 · Cited by 3,109
Habitat destruction and the extinction debt
Tilman, D., May, R. M., Lehman, C. L., & Nowak, M. A. (1994) · Nature · doi:10.1038/371065a0 · Cited by 2,844
Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data
Loveland, T. R., Reed, B. C., Brown, J. F., Ohlen, D. O., Zhu, Z., Yang, L., & Merchant, J. W. (2000) · International Journal of Remote Sensing · doi:10.1080/014311600210191 · Cited by 2,580
Climate change 1992 : the supplementary report to the IPCC scientific assessment
Houghton, J. T., Callander, B. A., & Varney, S. (1992) · Cited by 1,990
Earthworms, their ecology and relationships with soils and land use
Lee, K. E. (1985) · Medical Entomology and Zoology · Cited by 1,749
THE ECOLOGICAL CONSEQUENCES OF CHANGES IN BIODIVERSITY: A SEARCH FOR GENERAL PRINCIPLES101
Tilman, D. (1999) · Ecology · doi:10.1890/0012-9658(1999)080[1455:tecoci]2.0.co;2 · Cited by 1,746
Light-Gap Disturbances, Recruitment Limitation, and Tree Diversity in a Neotropical Forest
Hubbell, S. P., Foster, R. B., O'Brien, S. T., Harms, K. E., Condit, R., Wechsler, B., Wright, S. J., & de Lao, S. L. (1999) · Science · doi:10.1126/science.283.5401.554 · Cited by 1,537
An atlas of past and present pollen maps for Europe, 0-13,000 years ago
Huntley, B. J., & Birks, H. J. B. (1983) · Durham Research Online (Durham University) · Cited by 1,533
COMMUNITY INVASIBILITY, RECRUITMENT LIMITATION, AND GRASSLAND BIODIVERSITY
Tilman, D. (1997) · Ecology · doi:10.1890/0012-9658(1997)078[0081:cirlag]2.0.co;2 · Cited by 1,462
Cited by
Prasad, A. M., Iverson, L. R., & Liaw, A. (2006) · Ecosystems · doi:10.1007/s10021-005-0054-1 · Cited by 1,987
Climate Impacts on Agriculture: Implications for Crop Production
Hatfield, J. L., Boote, K. J., Kimball, B. A., Ziska, L. H., Izaurralde, R. C., Ort, D., Thomson, A. M., & Wolfe, D. (2011) · Agronomy Journal · doi:10.2134/agronj2010.0303 · Cited by 1,645
Climate change impacts and adaptation in forest management: a review
Keenan, R. J. (2015) · Annals of Forest Science · doi:10.1007/s13595-014-0446-5 · Cited by 675
MOLECULAR INDICATORS OF TREE MIGRATION CAPACITY UNDER RAPID CLIMATE CHANGE
McLachlan, J. S., Clark, J. S., & Manos, P. S. (2005) · Ecology · doi:10.1890/04-1036 · Cited by 630
Adapt or disperse: understanding species persistence in a changing world
BERG, M. P., KIERS, E. T., DRIESSEN, G., Van Der HEIJDEN, M., KOOI, B. W., KUENEN, F., LIEFTING, M., VERHOEF, H. A., & ELLERS, J. (2010) · Global Change Biology · doi:10.1111/j.1365-2486.2009.02014.x · Cited by 616
Metadata
- Authors
- Malcolm, J. R., Markham, A., Neilson, R. P., & Garaci, M.
- Venue
- Journal of Biogeography
- Publisher
- Wiley
- Published
- 2002-07
- Volume
- 29
- Issue
- 7
- Pages
- 835-849
- ISSN
- 0305-0270 (ISSN-L)
- 1365-2699
- OpenAlex
- W2169190286
- Cited by
- 373
- References
- 56
- FWCI
- 8.28
- 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: Estimated migration rates under scenarios of global climate change. https://app.cochat.ai/papers/10.1046/j.1365-2699.2002.00702.x
- The paper
- Malcolm, J. R., Markham, A., Neilson, R. P., & Garaci, M. (2002). Estimated migration rates under scenarios of global climate change. Journal of Biogeography. https://doi.org/10.1046/j.1365-2699.2002.00702.x
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.