Abstract
Climate warming is expected to increase the energy demands of ectotherms by accelerating their metabolic rates exponentially. However, this prediction ignores environmental complexity such as species interactions. Here, to better understand the metabolic costs of climate change for ectotherms, we reared three Drosophila species in either single-species or two-species cultures at different temperatures and projected adult metabolic responses under an intermediate climate-warming scenario across the global range of Drosophila. We determined that developmental acclimation to warmer temperatures can reduce the energetic cost of climate warming from 39% to ~16% on average by reducing the thermal sensitivity of metabolic rates. However, interspecific interactions among larvae can erode this benefit of developmental thermal acclimation by increasing the activity of adults that develop at warmer temperatures. Thus, by ignoring species interactions we risk underestimating the metabolic costs of warming by 3–16% on average.
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Data availability
Drosophila occurrence records were downloaded from https://www.gbif.org/ using the R package rgbif v.3.7.3 (GBIF Occurrence Download https://doi.org/10.15468/dl.8aymsf, accessed on 17 March 2022)45. Recent climate data (1970–2000) were downloaded from WorldClim v.2.1 (ref. 46) (https://worldclim.org/) using the R package raster v.3.6-3 (ref. 47). Projected future climate data (2081–2100) under the SSP 2-4.5 scenario (CMIP6) for eight global climate models (BCC-CSM2-MR, CanESM5, CNRM-CM6-1, CNRM-ESM2-1, IPSL-CM6A-LR, MIROC-ES2L, MIROC6 and MRI-ESM2-0) were downloaded manually from WorldClim v.2.1 (ref. 46). All other data generated and analysed during the current study are available in the Zenodo repository, https://doi.org/10.5281/zenodo.7475922 (ref. 48).
Code availability
R code used for data analysis is available in the Zenodo repository, https://doi.org/10.5281/zenodo.7475922 (ref. 48).
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Acknowledgements
C. White provided equipment and R code49, C. Sgrò provided access to fly stocks, T. Thomason assisted with fly maintenance and data collection and C. Bywater assisted with data extraction. L.A.A. and V.K. were funded by a Monash University Faculty of Science Advancing Women’s Success Grant (L.A.A. and V.K.) and the Australian Research Council (DE14100141 (V.K.), DP180103925 (L.A.A.), FT200100703 (V.K.) and DP220103421 (L.A.A.)).
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L.A.A. and V.K. conceived and designed the study, performed the experiments, analysed the data and wrote the paper. L.A.A. performed the modelling.
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Nature Climate Change thanks Paul Huxley, Tommy Norin, Mélanie Thierry, Mathieu Videlier and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Extended data
Extended Data Fig. 1 Conceptual diagram describing the thermal sensitivities of metabolic rate.
The thermal sensitivity of metabolic rate can be described by the factorial change in metabolic rate relative to a 10°C change in temperature (Q10). The metabolic rates of ectotherms acclimated to cold (blue line) and warm (red line) temperatures accelerate approximately exponentially with acute increases in temperature as described by the acute Q10. Acclimation to warmer temperatures causes a shift to the right in the reaction norm for metabolic rate. When measured at the same temperature, warm-acclimated ectotherms have lower metabolic rates than cold-acclimated ectotherms as described by the acclimation Q10. When cold- and warm- acclimated ectotherms are measured at their respective acclimation temperatures, the thermal sensitivity of metabolic rate can be described by the post-acclimation Q10. The post-acclimation Q10 therefore describes the sensitivity of metabolic rate to changes in temperature that last longer than several days and thus describes how acclimation to warmer temperatures opposes the acute thermodynamic effect of temperature on metabolic rate. The post-acclimation Q10 is therefore lower than the acute Q10.
Extended Data Fig. 2 Absolute metabolic cost of interspecific interactions under climate warming.
Spatially explicit predictions of the absolute metabolic cost (mW g-0.75) of interspecific interactions at the end of the century under an intermediate climate-warming scenario across the global range of Drosophila (n = 1,944,000). Changes in temperature (a) at each location were calculated between recent (1970–2000) and projected future (2081–2100) climates using the mean temperature of the warmest quarter at a 10 arcmin resolution. The warmest quarter is assumed to be when Drosophila are most active. Future temperatures were extracted from climate projections (CMIP Phase 6) based on eight global climate models (BCC-CSM2-MR, CanESM5, CNRM-CM6-1, CNRM-ESM2-1, IPSL-CM6A-LR, MIROC-ES2L, MIROC6 and MRI-ESM2-0) under the Shared Socio-Economic Pathway 2–4.5 scenario. Predictions are based on the thermal sensitivities of the routine metabolic rate (described by Q10 values) of Drosophila melanogaster (Mel) (b, c) and D. simulans (Sim) (d) (abbreviated name in bold) following developmental thermal acclimation in single-species or two-species cultures with a heterospecific (Heterosp.) (abbreviated name not in bold). For Mel, the heterospecific was either Sim or D. sulfurigaster (Sulf). For Sim, the heterospecific was Mel. Metabolic costs of interspecific interactions under climate warming are expressed as the absolute difference between predicted metabolic rates with and without interspecific interactions in units of mW g-0.75 (see Eq. 8 in Methods). Predictions are constrained to within 200 km of occurrence localities. Data are summarized for each region with boxes showing the interquartile range (IQR), lines within boxes showing the median, whiskers showing the 1.5×IQR range, and data points are the mean (Arctic: n = 304,560; north temperate: n = 559,440; tropics: n = 604,800; south temperate: 475,200). Outliers are excluded from box plots for visual clarity. Coastline data from mapdata v2.3.036.
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Alton, L.A., Kellermann, V. Interspecific interactions alter the metabolic costs of climate warming. Nat. Clim. Chang. 13, 382–388 (2023). https://doi.org/10.1038/s41558-023-01607-6
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DOI: https://doi.org/10.1038/s41558-023-01607-6
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