Patchy field sampling biases understanding of climate change impacts across the Arctic

Abstract

Effective societal responses to rapid climate change in the Arctic rely on an accurate representation of region-specific ecosystem properties and processes. However, this is limited by the scarcity and patchy distribution of field measurements. Here, we use a comprehensive, geo-referenced database of primary field measurements in 1,840 published studies across the Arctic to identify statistically significant spatial biases in field sampling and study citation across this globally important region. We find that 31% of all study citations are derived from sites located within 50 km of just two research sites: Toolik Lake in the USA and Abisko in Sweden. Furthermore, relatively colder, more rapidly warming and sparsely vegetated sites are under-sampled and under-recognized in terms of citations, particularly among microbiology-related studies. The poorly sampled and cited areas, mainly in the Canadian high-Arctic archipelago and the Arctic coastline of Russia, constitute a large fraction of the Arctic ice-free land area. Our results suggest that the current pattern of sampling and citation may bias the scientific consensuses that underpin attempts to accurately predict and effectively mitigate climate change in the region. Further work is required to increase both the quality and quantity of sampling, and incorporate existing literature from poorly cited areas to generate a more representative picture of Arctic climate change and its environmental impacts.

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Fig. 1: Sampling location and citation density.
Fig. 2: Distribution of research citations for MAT versus ∆MAT and fAPAR versus ∆fAPAR.
Fig. 3: Differences between sampled conditions and actual conditions.

References

  1. 1.

    ACIA Impacts of a Warming Arctic (Cambridge Univ. Press, Cambridge, 2004).

  2. 2.

    Larsen, J. N. et al. in Climate Change 2014: Impacts, Adaptation, and Vulnerability (eds Field, C.B. et al.) 1567–1612 (IPCC, Cambridge Univ. Press, Cambridge, New York, 2014).

  3. 3.

    Rustad, L. et al. A meta-analysis of the response of soil respiration, net nitrogen mineralization, and aboveground plant growth to experimental ecosystem warming. Oecologia 126, 543–562 (2001).

    CAS  Article  Google Scholar 

  4. 4.

    Tape, K., Sturm, M. & Racine, C. The evidence for shrub expansion in northern Alaska and the pan-Arctic effects of temperature and substrate quality on element mineralization in six Arctic soils. Glob. Change Biol. 12, 686–702 (2006).

    Article  Google Scholar 

  5. 5.

    Nadelhoffer, K. J., Giblin, A. E., Shaver, G. R. & Laundre, J. A. Effects of temperature and substrate quality on element mineralization in six Arctic soils. Ecology 72, 242–253 (1991).

    Article  Google Scholar 

  6. 6.

    Walker, M. D. et al. Plant community responses to experimental warming across the tundra biome. Proc. Natl Acad. Sci. USA 103, 1342–1346 (2006).

    CAS  Article  Google Scholar 

  7. 7.

    Nuttal, P. Protecting the Arctic: Indigenous Peoples and Cultural Survival (Harwood Academic, Amsterdam, 1998).

  8. 8.

    Martin, L. J., Blossey, B. & Ellis, E. Mapping where ecologists work: biases in the global distribution of terrestrial ecological observations. Front. Ecol. Environ. 10, 195–201 (2012).

    Article  Google Scholar 

  9. 9.

    Magliocca, N. R. et al. Synthesis in land change science: methodological patterns, challenges, and guidelines. Reg. Environ. Change 15, 211–226 (2015).

    Article  Google Scholar 

  10. 10.

    Sotomayor, D. A. & Lortie, C. J. Indirect interactions in terrestrial plant communities: emerging patterns and research gaps. Ecosphere 6, 103 (2015).

    Article  Google Scholar 

  11. 11.

    Bellard, C. & Jeschke, J. M. A spatial mismatch between invader impacts and research publications. Conserv. Biol. 30, 230–232 (2016).

    CAS  Article  Google Scholar 

  12. 12.

    Dos Santos, J. G., Malhado, A. C. M., Ladle, R. J., Correia, R. A. & Costa, M. H. Geographic trends and information deficits in Amazonian conservation research. Biol. Conserv. 24, 2853–2863 (2015).

    Google Scholar 

  13. 13.

    Human Health in the Arctic (AMAP, Oslo, 2009).

  14. 14.

    Petersen, A. M. et al. Reputation and impact in academic careers. Proc. Natl Acad. Sci. USA 111, 15316–15321 (2013).

    Article  Google Scholar 

  15. 15.

    Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Clim. 25, 1965–1978 (2005).

    Article  Google Scholar 

  16. 16.

    Taylor, K. E. et al. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2011).

    Article  Google Scholar 

  17. 17.

    Zhu, Z. et al. Global data sets of vegetation leaf area index (LAI) 3g and fraction of photosynthetically active radiation (FPAR) 3g derived from global inventory modeling and mapping studies (GIMMS) normalized difference vegetation index (NDVI3g) for the period 1981 to 2011. Remote Sens. 5, 927–948 (2013).

    Article  Google Scholar 

  18. 18.

    Myneni, R. B. et al. Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sens. Environ. 83, 214–231 (2002).

    Article  Google Scholar 

  19. 19.

    Post, E. et al. Ecological dynamics across the Arctic associated with recent climate change. Science 325, 1365–1358 (2009).

    Article  Google Scholar 

  20. 20.

    La Puma, I. P. et al. Relating NDVI to ecosystem CO2 exchange patterns in response to season length and soil warming manipulations in Arctic Alaska. Remote Sens. Environ. 109, 225–236 (2007).

    Article  Google Scholar 

  21. 21.

    Myers-Smith, I. H. et al. Climate sensitivity of shrub growth across the tundra biome. Nat. Clim. Change 5, 887–891 (2015).

    Article  Google Scholar 

  22. 22.

    Hugelius, G. et al. A new data set for estimating organic carbon storage to 3 m depth in soils of the northern circumpolar permafrost region. Earth Syst. Sci. Data 5, 393–402 (2013).

    Article  Google Scholar 

  23. 23.

    Burke, E. J., Hartley, I. P. & Jones, C. D. Uncertainties in the global temperature change caused by carbon release from permafrost thawing. Cryosphere 6, 1063–1076 (2012).

    Article  Google Scholar 

  24. 24.

    Shaver, G. R. & Jonasson, S. Response of Arctic ecosystems to climate change: results of long-term field experiments in Sweden and Alaska. Polar Res. 18, 245–252 (1999).

    Article  Google Scholar 

  25. 25.

    Hughes, B. B. et al. Long-term studies contribute disproportionately to ecology and policy. BioScience 67, 271–281 (2017).

    Article  Google Scholar 

  26. 26.

    Moher, D., Liberati, A., Tetzlaff, J. & Altman, D. G. & the PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 6, e1000097 (2009).

    Article  Google Scholar 

  27. 27.

    Getis, A. & Ord, J. K. The analysis of spatial association by use of distance statistics. Geogr. Anal. 24, 189–206 (1992).

    Article  Google Scholar 

  28. 28.

    Ord, J. K. & Getis, A. Local spatial autocorrelation statistics: distributional issues and an application. Geogr. Anal. 27, 286–306 (1995).

    Article  Google Scholar 

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Acknowledgements

This work was supported by an Action Group grant awarded to D.B.M. (F 2016 / 668) by the Lund University Strategic Research Area ‘biodiversity and ecosystem services in a changing climate’. The manuscript benefitted from comments made by B. Smith and T. Christensen (Lund University), and help with analysis from S. Olsson (Lund University).

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D.B.M. conceived of the study, reviewed papers, analysed the data and wrote the paper. A.M.A. processed the bioclimatic data, and conducted the spatial analyses and mapping. A.T.C., B.B.K., C.C., D.B., J.A., J.A.K., J.R.M., J.P., M.Becker, M.Berggren, M.J., M.K.S., N.C., N.J.H., R.A.S., T.D.G.H., J.T., K.P. and W.Z. reviewed papers and provided comments on manuscript drafts. A.A. processed bioclimatic data and provided comments on manuscript drafts. D.E.T. performed the geo-statistical analyses and provided comments on manuscript drafts. G.W., H.L., J.R., J.U., M.P.B. and R.G.B. assisted with formulation of the proposal, resulting in the grant that supported this work, and provided comments on manuscript drafts.

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Correspondence to Daniel B. Metcalfe.

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The authors declare no competing interests.

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Supplementary Tables 1–2, Supplementary Figures 1–13

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Metcalfe, D.B., Hermans, T.D.G., Ahlstrand, J. et al. Patchy field sampling biases understanding of climate change impacts across the Arctic. Nat Ecol Evol 2, 1443–1448 (2018). https://doi.org/10.1038/s41559-018-0612-5

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