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Macroclimate data overestimate range shifts of plants in response to climate change


Current conservation policy has been shaped by the expectation that, for many species, places with suitable climate will lie outside their current range, thus leading to predictions of numerous extinctions. Here we show that the magnitude of range shifts is often overestimated as climate data used do not reflect the microclimatic conditions that many organisms experience. We model the historic (1977–1995) distributions of 244 heathland and grassland plant taxa using both macro- and microclimate data and project these distributions to present day (2003–2021). Whereas macroclimate models predicted major range shifts (median 14 km shift), microclimate models predicted localized shifts, generally of less than 1 km, into favourable microclimates that more closely match observed patterns of establishment and extirpation. Thus, improving protection of refugial populations within species’ existing geographic range may, for species living in environments exposed to sunlight, be more effective than assisted translocations and overhaul of protected area networks.

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Fig. 1: Microclimate and range shifts.
Fig. 2: Range shifts predicted using macro- and microclimate data.
Fig. 3: Suitability predicted using macro- and microclimate.
Fig. 4: Shifts in climatically suitable conditions predicted using macro- and microclimate data.

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Data availability

The global gridded 0.5° climate dataset is available from The UK gridded climate dataset is available from Datasets required to generate the 100-m-resolution gridded climate dataset for the Lizard Peninsula are included with R package microclima16 available from Plant distribution datasets required to run the models are published online38. Forest-cover datasets are publicly available from UKCEH53 and

Code availability

All data and code used for the analysis are available on request from the corresponding author and are published online38. The microclima16 R package is available from


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We thank K. Gaston for helpful comments. I.M.D.M. was supported by the Natural Environment Research Council (NE/L00268X/1).

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Authors and Affiliations



I.M.D.M. and E.R. conceived and designed the study. I.M.D.M. performed the numerical analysis and wrote the paper with contributions from E.R. Both authors discussed and interpreted results.

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Correspondence to Ilya M. D. Maclean.

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Nature Climate Change thanks Jonas Lembrechts, Jonathan Lenoir, Martin Macek and Helen Slater for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Range shifts predicted using macro- and microclimate data.

Here results are shown without forest grid cells masked. Top: how far taxa would need to move in order to track climatic changes. Here the mean distances between each grid cell predicted to be occupied historically (1977–1995) and the nearest location with climatically suitable conditions under recent condition (2003–2021) is predicted using (a) 0.5° and (b) 5 km grid resolution macroclimate data and (c) 100 m grid resolution microclimate data for each of 244 plant taxa. Bottom: here the magnitude and direction of the shift in the suitability-weighted centroid of each taxa’s distribution is shown, modelled at (d) 0.5°, (e) 5 km resolution and (f) 100 m resolution.

Extended Data Fig. 2 Range shifts predicted using macro- and microclimate data (forest cells not masked).

Mean distances between each grid cell predicted to be occupied recently (2003–2021) to the nearest location with climatically suitable conditions historically (1977–1995) predicted using (a) 0.5° and (b) 5 km grid resolution macroclimate data and (c) 100 m grid resolution microclimate data for each of 244 plant taxa.

Extended Data Fig. 3 Range shifts predicted using macro- and microclimate data (additional models).

ad, Mean distances between each grid cell predicted to be occupied historically (1977–1995) and the nearest location with climatically suitable conditions under recent condition (2003–2021). eh, The magnitude and direction of the shift in the suitability-weighted centroid of each taxa’s distribution. a,e, Results for Erica tetralix modelled at 100 m resolution at each of 73 sites. b,f, The results for all taxa modelled at 0.5° grid resolution, but using temperature estimates for 5 cm above ground. c,g, Results for models fitted across Europe and projected to the Lizard Peninsula (temperature estimates 5 cm above ground). d,h, Results for the Lizard Peninsula using temperature estimates at the height of a standard weather station.

Extended Data Fig. 4 Suitability predicted using macro- and microclimate (forest grid cells not masked).

In (a) and (b) the relationship between the current (2003–2021) and historic (1977–1995) predicted probability of occurrence on the Lizard Peninsula is shown for all taxa, demonstrating that when microclimate (green) data are used, the relationship is shallower than when macroclimate (purple) data are used. In consequence, when modelled using microclimate data, fewer extirpations are predicted. The green and purple dashed lines are the line-of-best fit for the modelled relationship for microclimate and macroclimate respectively. In (a) macroclimate occurrence is derived from 0.5° grid resolution models and in (b) from 5 km grid resolution models. In (c) the relationship between the current (2003–2021) and historic (1977–1995) predicted probability of occurrence of Erica tetralix is shown in every grid cell with a predicted probability of occurrence >0.1 across Europe (purple) and for each 100 m grid cell with a historic record in each of 73 40 × 40 km selected focal areas (green).

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Maclean, I.M.D., Early, R. Macroclimate data overestimate range shifts of plants in response to climate change. Nat. Clim. Chang. 13, 484–490 (2023).

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