Convergence of terrestrial plant production across global climate gradients

A Corrigendum to this article was published on 18 May 2016

This article has been updated

Abstract

Variation in terrestrial net primary production (NPP) with climate is thought to originate from a direct influence of temperature and precipitation on plant metabolism. However, variation in NPP may also result from an indirect influence of climate by means of plant age, stand biomass, growing season length and local adaptation. To identify the relative importance of direct and indirect climate effects, we extend metabolic scaling theory to link hypothesized climate influences with NPP, and assess hypothesized relationships using a global compilation of ecosystem woody plant biomass and production data. Notably, age and biomass explained most of the variation in production whereas temperature and precipitation explained almost none, suggesting that climate indirectly (not directly) influences production. Furthermore, our theory shows that variation in NPP is characterized by a common scaling relationship, suggesting that global change models can incorporate the mechanisms governing this relationship to improve predictions of future ecosystem function.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: Global variation in annual net primary production for 1,247 woody plant communities grouped by age class.
Figure 2: Net primary production of woody plant communities across global climate gradients.
Figure 3: Global variation in annual net primary production of woody plant communities expressed as a general scaling function of plant age a and stand biomass Mtot.
Figure 4: Partial regression plots illustrating relationships between monthly net primary production (NPP/lgs) and individual covariates from equation (4) for 1,247 woody plant communities.

Change history

  • 06 August 2014

    Figure 3 y-axis label was incorrect and has been fixed.

References

  1. 1

    Schimel, D. S. et al. Recent patterns and mechanisms of carbon exchange by terrestrial ecosystems. Nature 414, 169–172 (2001)

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  2. 2

    Lieth, H. in Primary Productivity of the Biosphere (eds Lieth, H. & Whittaker, R. H. ) (Springer, 1975)

    Google Scholar 

  3. 3

    Schuur, E. A. G. Productivity and global climate revisited: The sensitivity of tropical forest growth to precipitation. Ecology 84, 1165–1170 (2003)

    Article  Google Scholar 

  4. 4

    Huxman, T. E. et al. Convergence across biomes to a common rain-use efficiency. Nature 429, 651–654 (2004)

    ADS  CAS  Article  Google Scholar 

  5. 5

    Ponce Campos, G. E. et al. Ecosystem resilience despite large-scale altered hydroclimatic conditions. Nature 494, 349–352 (2013)

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  6. 6

    Berry, J. & Bjorkman, O. Photosynthetic response and adaptation to temperature in higher plants. Annu. Rev. Plant Physiol. 31, 491–543 (1980)

    Article  Google Scholar 

  7. 7

    Enquist, B. J., Kerkhoff, A. J., Huxman, T. E. & Economo, E. P. Adaptive differences in plant physiology and ecosystem paradoxes: insights from metabolic scaling theory. Glob. Change Biol. 13, 591–609 (2007)

    ADS  Article  Google Scholar 

  8. 8

    Kerkhoff, A. J., Enquist, B. J., Elser, J. J. & Fagan, W. F. Plant allometry, stoichiometry and the temperature-dependence of primary productivity. Glob. Ecol. Biogeogr. 14, 585–598 (2005)

    Article  Google Scholar 

  9. 9

    Bonan, G. B. Physiological derivation of the observed relationship between net primary production and mean annual air temperature. Tellus B Chem. Phys. Meterol. 45, 397–408 (1993)

    ADS  Article  Google Scholar 

  10. 10

    Chapin, F. S. Effects of plant traits on ecosystem and regional processes: A conceptual framework for predicting the consequences of global change. Ann. Bot. (Lond.) 91, 455–463 (2003)

    Article  Google Scholar 

  11. 11

    Enquist, B. J., West, G. B. & Brown, J. H. Extensions and evaluations of a general quantitative theory of forest structure and dynamics. Proc. Natl Acad. Sci. USA 106, 7046–7051 (2009)

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  12. 12

    West, G. B., Enquist, B. J. & Brown, J. H. A general quantitative theory of forest structure and dynamics. Proc. Natl Acad. Sci. USA 106, 7040–7045 (2009)

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  13. 13

    Enquist, B. J. et al. A general integrative model for scaling plant growth, carbon flux, and functional trait spectra. Nature 449, 218–222 (2007)

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  14. 14

    Brown, J. H., Gillooly, J. F., Allen, A. P., Savage, V. M. & West, G. B. Toward a metabolic theory of ecology. Ecology 85, 1771–1789 (2004)

    Article  Google Scholar 

  15. 15

    Allen, A. P., Gillooly, J. F. & Brown, J. H. Linking the global carbon cycle to individual metabolism. Funct. Ecol. 19, 202–213 (2005)

    Article  Google Scholar 

  16. 16

    Enquist, B. J. & Bentley, L. P. in Metabolic Ecology: A Scaling Approach (eds Sibly, R. M., Brown, S. & Kodric-Brown, A. ) 164–187 (Wiley, 2012)

    Google Scholar 

  17. 17

    Gates, D. M. Biophysical Ecology (Springer, 1980)

    Google Scholar 

  18. 18

    Helliker, B. R. & Richter, S. L. Subtropical to boreal convergence of tree-leaf temperatures. Nature 454, 511–514 (2008)

    ADS  CAS  PubMed  Article  Google Scholar 

  19. 19

    Atkin, O. K. & Tjoelker, M. G. Thermal acclimation and the dynamic response of plant respiration to temperature. Trends Plant Sci. 8, 343–351 (2003)

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  20. 20

    New, M., Lister, D., Hulme, M. & Makin, I. A high-resolution data set of surface climate over global land areas. Clim. Res. 21, 1–25 (2002)

    Article  Google Scholar 

  21. 21

    Monteith, J. L. Climate and the efficiency of crop production in Britain. Phil. Trans. R. Soc. Lond. B 281, 277–294 (1977)

    ADS  Article  Google Scholar 

  22. 22

    Renee Brooks, J., Barnard, H. R., Coulombe, R. & McDonnell, J. J. Ecohydrologic separation of water between trees and streams in a Mediterranean climate. Nature Geosci. 3, 100–104 (2010)

    ADS  CAS  Article  Google Scholar 

  23. 23

    Gower, S. T., McMurtrie, R. E. & Murty, D. Aboveground net primary production decline with stand age: potential causes. Trends Ecol. Evol. 11, 378–382 (1996)

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  24. 24

    Ryan, M. G. & Yoder, B. J. Hydraulic limits to tree height and tree growth. Bioscience 47, 235–242 (1997)

    Article  Google Scholar 

  25. 25

    DeLucia, E. H., Drake, J. E., Thomas, R. B. & Gonzalez-Meler, M. Forest carbon use efficiency: is respiration a constant fraction of gross primary production? Glob. Change Biol. 13, 1157–1167 (2007)

    ADS  Article  Google Scholar 

  26. 26

    Kerkhoff, A. J. & Enquist, B. J. Ecosystem allometry: the scaling of nutrient stocks and primary productivity across plant communities. Ecol. Lett. 9, 419–427 (2006)

    PubMed  Article  PubMed Central  Google Scholar 

  27. 27

    Muller-Landau, H. C. et al. Testing metabolic ecology theory for allometric scaling of tree size, growth, and mortality in tropical forests. Ecol. Lett. 9, 575–588 (2006)

    PubMed  Article  PubMed Central  Google Scholar 

  28. 28

    Niklas, K. J., Midgley, J. J. & Rand, R. H. Tree size frequency distributions, plant density, age and community disturbance. Ecol. Lett. 6, 405–411 (2003)

    Article  Google Scholar 

  29. 29

    Yvon-Durocher, G. et al. Reconciling the temperature dependence of respiration across timescales and ecosystem types. Nature 487, 472–476 (2012)

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  30. 30

    Wright, I. J. & Westoby, M. Differences in seedling growth behaviour among species: trait correlations across species, and trait shifts along nutrient compared to rainfall gradients. J. Ecol. 87, 85–97 (1999)

    Article  Google Scholar 

  31. 31

    Kempes, C. P., West, G. B., Crowell, K. & Girvan, M. Predicting maximum tree heights and other traits from allometric scaling and resource limitations. PLoS ONE 6, e20551 (2011)

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  32. 32

    Stegen, J. C. et al. Variation in above-ground forest biomass across broad climatic gradients. Glob. Ecol. Biogeogr. 20, 744–754 (2011)

    Article  Google Scholar 

  33. 33

    Larjavaara, M. & Muller-Landau, H. C. Rethinking the value of high wood density. Funct. Ecol. 24, 701–705 (2010)

    Article  Google Scholar 

  34. 34

    Stephenson, N. L. et al. Rate of tree carbon accumulation increases continuously with tree size. Nature 507, 90–93 (2014)

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  35. 35

    Cannell, M. G. R. World Forest Biomass and Primary Production Data (Academic, 1982)

    Google Scholar 

  36. 36

    Luo, T. X. Patterns of Biological Production and its Mathematical Models for Main Forest Types of China. PhD thesis, Chinese Academy of Sciences. (1996)

  37. 37

    Clark, D. S. et al. Net primary productivity in tropical forests: An evaluation and synthesis of existing field data. Ecol. Appl. 11, 371–384 (2001)

    Article  Google Scholar 

  38. 38

    Luyssaert, S. et al. CO2 balance of boreal, temperate, and tropical forests derived from a global database. Glob. Change Biol. 13, 2509–2537 (2007)

    ADS  Article  Google Scholar 

  39. 39

    Whittaker, R. H. Communities and Ecosystems (Macmillan, 1970)

    Google Scholar 

  40. 40

    Cairns, M. A., Brown, S., Helmer, E. H. & Baumgardner, G. A. Root biomass allocation in the world's upland forests. Oecologia 111, 1–11 (1997)

    ADS  PubMed  Article  PubMed Central  Google Scholar 

  41. 41

    Vieira, S. et al. Slow growth rates of Amazonian trees: Consequences for carbon cycling. Proc. Natl Acad. Sci. USA 102, 18502–18507 (2005)

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  42. 42

    Häsler, R., Streule, A. & Turner, H. Shoot and root growth of young Larix decidua in contrasting microenvironments near the Alpine timberline. Phyton 39, 47–52 (1999)

    Google Scholar 

  43. 43

    Fredlund, D. G., Rahardjo, H. & Fredlund, M. D. Unsaturated Soil Mechanics in Engineering Practice (Wiley, 2012)

    Google Scholar 

  44. 44

    FAO/IIASA/ISRIC/ISSCAS/JRC. Harmonized World Soil Database (version 1.2) (FAO and IIASA, 2012)

  45. 45

    Huston, M. A. Precipitation, soils, NPP, and biodiversity: resurrection of Albrecht's curve. Ecol. Monogr. 82, 277–296 (2012)

    Article  Google Scholar 

  46. 46

    R Development Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2011)

  47. 47

    Warton, D. I., Duursma, R. A., Falster, D. S. & Taskinen, S. smatr 3– an R package for estimation and inference about allometric lines. Methods Ecol. Evol. 3, 257–259 (2012)

    Article  Google Scholar 

  48. 48

    Brett, M. T. When is a correlation between non-independent variables “spurious”? Oikos 105, 647–656 (2004)

    Article  Google Scholar 

  49. 49

    Ryan, T. P. Modern Regression Methods (Wiley, 1997)

    Google Scholar 

Download references

Acknowledgements

S.T.M. and B.J.E. were supported by an NSF MacroSystems award (1065861) and a fellowship from the Aspen Center for Environmental Studies. D.C. was supported by the National Natural Science Foundation of China (31170374 and 31370589) and Fujian Natural Science Funds for Distinguished Young Scholar (2013J06009). A.J.K. was supported by a sabbatical supplement from Kenyon College, and by a National Science Foundation ROA supplement (1065861) to the NSF MacroSystems award (1065861) to B.J.E.

Author information

Affiliations

Authors

Contributions

S.T.M., D.C., A.J.K. and B.J.E. compiled data, developed theory, performed analyses and wrote the paper.

Corresponding authors

Correspondence to Dongliang Cheng or Brian J. Enquist.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Partial residual plots showing linearization of NPP relationships by power and exponential transforms of precipitation and plant age.

Relationships were best linearized by power transforms of both precipitation and age, so power laws were used to characterize precipitation- and age-dependence of NPP in Supplementary Information Equation (S6). Multiple regression models used average growing season temperatures <1/kT>gs and mean growing season precipitation Pgs, but similar results were observed using mean annual estimates. Dashed line, OLS linear regression line; solid line, Loess smooth. a, b, Power transform for precipitation and age; c, d, power transform for precipitation and exponential transform for age; e, f, exponential transform for precipitation and power transform for age; g, h, exponential transform for precipitation and age.

Extended Data Figure 2 Relationship between mean annual temperature and growing season length (r2 = 0.853, P < 2.2 × 10−16).

Extended Data Figure 3 Partial regression plots showing relationships between annual net primary production (NPP) and each covariate.

Both variables in each plot are residuals. Plots show the correct relationship (slope and variance) between NPP and each covariate while controlling for the influence of all other model covariates. All relationships were significant at α = 0.001, except for growing season length (P = 0.026). However, total stand biomass and plant age explained most of the variation in NPP, while temperature, growing season length, and mean annual precipitation each explained less than 10% of the variation (Table 1). a, Relationship between NPP and average growing season temperature <1/kT>gs. b, Relationship between NPP and mean growing season precipitation Pgs. c, Relationship between NPP and growing season length lgs. d, Relationship between NPP and total stand biomass Mtot. e, Relationship between NPP and plant age a.

Extended Data Figure 4 Global variation in annual net primary production (NPP) for 1,247 forest stands expressed as a general scaling function of age a and total stand biomass Mtot.

Stands grouped according to standard biome definitions39. Grey, desert; light orange, savannah; light blue, temperate forest; black, temperate rainforest; yellow, taiga; dark blue, tropical rainforest; dark orange, tropical seasonal forest; pink, tundra; green, woodland/shrubland.

Extended Data Table 1 Bivariate regression fits of net primary production on temperature and precipitation data for 1,247 woody plant communities
Extended Data Table 2 Standardized major axis (SMA) regression fits of annual net primary production (NPP) on stand biomass for 1,247 woody plant communities
Extended Data Table 3 Multiple regression fits of metabolic scaling theory for terrestrial net primary production (equations (3) and (4)) to a global compilation of data for root (subscript R; 1,236 stands), aboveground woody (subscript AGW; 1,233 stands) and foliage (subscript F; 1,234 stands) components of net primary production

Supplementary information

Supplementary Information

This file contains Supplementary Text and Data and Supplementary References. (PDF 172 kb)

PowerPoint slides

Source data

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Michaletz, S., Cheng, D., Kerkhoff, A. et al. Convergence of terrestrial plant production across global climate gradients. Nature 512, 39–43 (2014). https://doi.org/10.1038/nature13470

Download citation

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing