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Geographical limits to species-range shifts are suggested by climate velocity

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The reorganization of patterns of species diversity driven by anthropogenic climate change, and the consequences for humans1, are not yet fully understood or appreciated2,3. Nevertheless, changes in climate conditions are useful for predicting shifts in species distributions at global4 and local scales5. Here we use the velocity of climate change6,7 to derive spatial trajectories for climatic niches from 1960 to 2009 (ref. 7) and from 2006 to 2100, and use the properties of these trajectories to infer changes in species distributions. Coastlines act as barriers and locally cooler areas act as attractors for trajectories, creating source and sink areas for local climatic conditions. Climate source areas indicate where locally novel conditions are not connected to areas where similar climates previously occurred, and are thereby inaccessible to climate migrants tracking isotherms: 16% of global surface area for 1960 to 2009, and 34% of ocean for the ‘business as usual’ climate scenario (representative concentration pathway (RCP) 8.5)8 representing continued use of fossil fuels without mitigation. Climate sink areas are where climate conditions locally disappear, potentially blocking the movement of climate migrants. Sink areas comprise 1.0% of ocean area and 3.6% of land and are prevalent on coasts and high ground. Using this approach to infer shifts in species distributions gives global and regional maps of the expected direction and rate of shifts of climate migrants, and suggests areas of potential loss of species richness.

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Figure 1: Climate-change features emerging from the properties of climate velocity trajectories using the Australian landmass as an example.
Figure 2: Global patterns of climate trajectory classes.
Figure 3: Regional patterns of climate velocity trajectory classes for land and sea surface temperatures.
Figure 4: Global and regional patterns of 50-year climate trajectory classes based on trends from ensembles of global climate models for 2006–2100.

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Change history

  • 26 March 2014

    Two labels in Fig. 1b, bottom part, were incorrect and have been fixed.


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This work was conducted as a part of the Towards Understanding Marine Biological Impacts of Climate Change Working Group supported by the National Center for Ecological Analysis and Synthesis, a center funded by the NSF (grant no. EF-0553768), the University of California, Santa Barbara and the State of California. M.T.B., P.J.M. and J.G.M. were supported by the UK Natural Environment Research Council grant NE/J024082/1. D.S. was supported by the Australian Research Council’s Collaborative Research Network. J.P. thanks the Australian Research Council Centre of Excellence for Coral Reef Studies for additional support, and A.J.R. was supported by the Australian Research Council Discovery Grant DP0879365 and Future Fellowship Grant FT0991722.

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Authors and Affiliations



M.T.B., D.S.S., A.J.R. and E.S.P. conceived the research. M.T.B., J.G.M. and D.S.S. analysed the data. M.T.B., D.S.S., A.J.R., E.S.P., J.G.M. and M.I.O. wrote the first draft. M.T.B., D.S.S., A.J.R., J.G.M., A.H., L.B.B., P.J.M., C.J.B., J.F.B., C.M.D., B.S.H., O.H.G., C.V.K.,W.K., M.I.O., J.M.P., C.P., W.J.S., S.F., K.J.W. and E.S.P. contributed equally to discussion of ideas and analyses, and all authors commented on the manuscript.

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Correspondence to Michael T. Burrows.

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The authors declare no competing financial interests.

Additional information

Data used in analyses are available from the University of East Anglia Climate Research Unit and the UK Meteorological Office Hadley Centre, with online access at the British Atmospheric Data Centre. Maps are available as Google Earth files on

Extended data figures and tables

Extended Data Figure 1 Ternary plots containing the trajectory classes.

ad, Plots are based on the proportions of trajectories starting from (Nst), ending in (Nend), and flowing through (NFT) a cell. In a ternary plot three-dimensional cell coordinates (adding up to a 100%) are projected in a two-dimensional space. The arrows by the axes indicate the direction in which each variable is projected into the trajectory space. Point clouds represent global 1° resolution cell coordinate projections into the trajectory space based on 50-year climate trajectory simulations for land (a) and sea surface temperature (b) (1960–2009), and 2006–2100 RCP 8.5 (c) and RCP 4.5 (d) climate scenarios for ocean temperatures. CON, convergence; DIV, divergence; SK, relative sink.

Extended Data Figure 2 Uncertainty associated with the proposed trajectory classification.

a, Mean standard error of the trend. b, Standard deviation in magnitude of spatial gradient. c, Angular deviation of the spatial gradient associated to bootstrapped (n = 500) mean annual surface temperature series. d, e, Bootstrap-derived uncertainty associated with the proposed trajectory classification (d) and after collapsing slow/non-moving and convergence/divergence areas into a single category each (e). rad, radians.

Extended Data Figure 3 Frequency distribution of the uncertainty associated with the trajectory-based classification of land and ocean.

a, Frequency histogram of the proportion of coincident categories between the proposed 1960–2009 trajectory classification and classifications resulting from 500 bootstrapped surface temperature climate series (see Methods for details). b, c, Cumulative frequency plots of the mean distribution of bootstrapped trajectory categories contained in each category of the proposed trajectory classification for land (b) and ocean regions (c).

Extended Data Figure 4 Global patterns of climate-velocity trajectory classes for ocean and land surface temperatures.

ad, Ocean surface temperatures (a, c) and land surface temperatures (b, d). Uncertainty in classification of areas is shown by the cross hatching on areas of original global patterns with 500 bootstrap class maps that are classified as ‘very likely’ (a, b; <90% consistency) and ‘likely’ (c, d; <66% consistency).

Extended Data Figure 5 Regional maps for the North and South Atlantic showing 50-year trajectories for the period 1960–2009.

a, North Atlantic b, South Atlantic. Trajectories are overlaid on corresponding classes of trajectory behaviour (Fig. 1).

Extended Data Figure 6 Regional maps for the North and South Pacific showing 50-year trajectories for the period 1960–2009.

a, North Pacific. b, South Pacific. Trajectories are overlaid on corresponding classes of trajectory behaviour (Fig. 1).

Extended Data Figure 7 Regional map for the Coral Triangle showing 50-year trajectories for the period 1960–2009.

Trajectories are overlaid on corresponding classes of trajectory behaviour (Fig. 1).

Extended Data Figure 8 Regional maps for Eurasia, Africa and South America showing 50-year trajectories for the period 1960–2009.

a, Eurasia. b, Africa. c, South America. Trajectories are overlaid on corresponding trajectory classes of trajectory behaviour (Fig. 1).

Extended Data Figure 9 Regional maps for North and Central America, and southeast Asia and Oceania showing 50-year trajectories for the period 1960–2009.

a, North and Central America. b, Southeast Asia and Oceania. Trajectories overlaid on corresponding classes of trajectory behaviour (Fig. 1).

Extended Data Table 1 Summary of trajectory classes, with implications for species range shifts if species distributions track shifting climatic niches

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Burrows, M., Schoeman, D., Richardson, A. et al. Geographical limits to species-range shifts are suggested by climate velocity. Nature 507, 492–495 (2014).

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