Skip to main content

Advertisement

Log in

Influence and predictive capacity of climate anomalies on daily to decadal extremes in canopy photosynthesis

  • Regular Paper
  • Published:
Photosynthesis Research Aims and scope Submit manuscript

Abstract

Significant advances have been made over the past decades in capabilities to simulate diurnal and seasonal variation of leaf-level and canopy-scale photosynthesis in temperate and boreal forests. However, long-term prediction of future forest productivity in a changing climate may be more dependent on how climate and biological anomalies influence extremes in interannual to decadal variability of canopy ecosystem carbon exchanges. These exchanges can differ markedly from leaf level responses, especially owing to the prevalence of long lags in nutrient and water cycling. Until recently, multiple long-term (10+ year) high temporal frequency (daily) observations of canopy exchange were not available to reliably assess this claim. An analysis of one of the longest running North American eddy covariance flux towers reveals that single climate variables do not adequately explain carbon exchange anomalies beyond the seasonal timescale. Daily to weekly lagged anomalies of photosynthesis positively autocorrelate with daily photosynthesis. This effect suggests a negative feedback in photosynthetic response to climate extremes, such as anomalies in evapotranspiration and maximum temperature. Moisture stress in the prior season did inhibit photosynthesis, but mechanisms are difficult to assess. A complex interplay of integrated and lagged productivity and moisture-limiting factors indicate a critical role of seasonal thresholds that limit growing season length and peak productivity. These results lead toward a new conceptual framework for improving earth system models with long-term flux tower observations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Amiro B, Barr AG, Barr JG et al (2010) Ecosystem carbon dioxide fluxes after disturbance in forests of North America. J Geophys Res 115:G00K02. doi:10.1029/2010JG001390

    Google Scholar 

  • Baldocchi DD (2008) Breathing of the terrestrial biosphere: lessons learned from a global network of carbon dioxide flux measurement systems. Aust J Bot 56:1–26

    Article  CAS  Google Scholar 

  • Baldocchi DD, Hutchison BA, Matt DR, McMillen RT (1985) Canopy radiative transfer models for spherical and known leaf inclination distribution angles: a test in an Oak-Hickory forest. J Appl Ecol 22:539–555

    Article  Google Scholar 

  • Baldocchi DD, Falge E, Wilson K (2001) A spectral analysis of biosphere-atmosphere trace gas flux densities and meteorological variables across hour to year time scales. Agric For Meteorol 107:1–27

    Article  Google Scholar 

  • Barnhart BL, Eichinger WE, Preuger JH (2012) Introducing an Ogive method for discontinuous data. Agric For Meteorol 162:58–62

    Article  Google Scholar 

  • Beer C et al (2010) Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate. Science 329:834–838. doi:10.1126/science.1184984

    Article  CAS  PubMed  Google Scholar 

  • Berger BW, Zhao CL, Davis KJ, Yi C, Bakwin PS (2001) Long-term carbon dioxide fluxes from a very tall tower in a northern forest: flux measurement methodology. J Atmos Ocean Technol 18:529–542

    Article  Google Scholar 

  • Booth BB et al (2012) High sensitivity of future global warming to land carbon cycle processes. Environ Res Lett 7:024002. doi:10.1088/1748-9326/7/2/024002

    Article  Google Scholar 

  • Bretherton CS, Widman M, Dymnikov VP, Wallace JM, Blade I (1999) The effective number of spatial degrees of freedom of a time-varying field. J Climate 12:1990–2009

    Google Scholar 

  • Carbone MS, Czimczik CI, McDuffee KE, Trumbore SE (2007) Allocation and residence time of photosynthetic products in a boreal forest using a low-level 14C pulse-chase labeling technique. Glob Change Biol 13:466–477

    Article  Google Scholar 

  • Collatz GJ, Ball JT, Grivet C, Berry JA (1991) Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer. Agric For Meteorol 54:107–136

    Article  Google Scholar 

  • Davis KJ, Bakwin PS, Yi C, Berger BW, Zhao C, Teclaw RM, Isebrands JG (2003) The annual cycles of CO2 and H2O exchange over northern mixed forest as observed from a very tall tower. Glob Change Biol 9:1278–1293

    Article  Google Scholar 

  • De Pury DGG, Farquhar GD (1997) Simple scaling of photosynthesis from leaves to canopies without the errors of big-leaf models. Plant Cell Environ 20:537–557

    Article  Google Scholar 

  • Desai AR (2010) Climatic and phenological controls on coherent regional interannual variability of carbon dioxide flux in a heterogeneous landscape. J Geophys Res 115:G00J02. doi:10.1029/2010JG001423

    Google Scholar 

  • Desai AR, Moorcroft PR, Bolstad PV, Davis KJ (2007) Regional carbon fluxes from a biometrically constrained dynamic ecosystem model: impact of disturbance, CO2 fertilization and heterogeneous land cover. J Geophys Res 112:G01017. doi:10.1029/2006JG000264

    Google Scholar 

  • Desai AR, Richardson AD, Moffat AM, Kattge J, Hollinger DY, Barr A, Falge E, Noormets A, Papale D, Reichstein M, Stauch VJ (2008) Cross site evaluation of eddy covariance GPP and RE decomposition techniques. Agric For Meteorol 148:821–838. doi:10.1016/j.agrformet.2007.11.012

    Article  Google Scholar 

  • Desai AR, Helliker BR, Moorcroft PR, Andrews AE, Berry JA (2010) Interannual variability in regional carbon fluxes from top-down and bottom-up perspectives. J Geophys Res 115:G02011. doi:10.1029/2009JG001122

    Google Scholar 

  • Detto M, Molini A, Katul G, Stoy P, Palmroth S, Baldocchi DD (2012) Causality and persistence in ecological systems: a nonparametric spectral granger causality approach. Am Nat 179:524–535

    Article  PubMed  Google Scholar 

  • Dietze MC et al (2011) Identifying the time scales that dominate model error: a North American synthesis of the spectral properties of ecosystem models. J Geophys Res 116:G04029. doi:10.1029/2011JG001661

    Google Scholar 

  • Farquhar GD, Sharkey TD (1982) Stomatal conductance and photosynthesis. Annu Rev Plant Physiol 33:317–345

    Article  CAS  Google Scholar 

  • Foken T, Aubinet M, Leuning R (2012) The eddy-covariance method. In: Aubinet M et al (eds) Eddy covariance: a practical guide to measurement and data analysis. Springer, Dordrecht, pp 1–19

    Chapter  Google Scholar 

  • Friedlingstein P, Cox P, Betts R et al (2006) Climate—carbon cycle feedback analysis, results from the C4MIP model intercomparison. J Clim 19:3337–3353

    Article  Google Scholar 

  • Gellesch E, Hein R, Jaeschke A, Beierkuhnlein C, Jentsch A (2013) Biotic interactions in the face of climate change. Prog Bot 74:321–349. doi:10.1007/978-3-642-30967-0_12

    Article  Google Scholar 

  • Heinsch FA, Zhao M, Running SW et al (2006) Evaluation of remote sensing based terrestrial productivity from MODIS using Ameriflux tower eddy flux network observations. IEEE Trans Geosci Remote 44:1908–1925. doi:10.1109/TGRS.2005.853936

    Article  Google Scholar 

  • Huang NE, Wu Z (2008) A review on Hilbert–Huang transform: method and its applications to geophysical studies. Rev Geophys 46:RG2006. doi:10.1029/2007RG000228

    Google Scholar 

  • Keenan TF et al (2012a) Evaluation of terrestrial biosphere model performance for land-atmosphere CO2 exchange on inter-annual time scales: results from the North American Carbon Program interim site synthesis. Glob Change Biol. doi:10.1111/j.1365-2486.2012.02678.x

    Google Scholar 

  • Keenan TF, Davidson E, Moffat A, Munger W, Richardson AD (2012b) Using model-data fusion to interpret past trends, and quantify uncertainties in future projections, of forest ecosystem carbon cycling. Glob Change Biol 18:2555–2569

    Article  Google Scholar 

  • Kumar M, Monteith JL (1981) Remote sensing of crop growth. In: Smith H (ed) Plants and the daylight spectrum. Academic Press, London, pp 133–144

    Google Scholar 

  • Le Quéré C, Raupach MR, Canadell JG et al (2009) Trends in the sources and sinks of carbon dioxide. Nat Geosci. doi:10.1038/ngeo689

    Google Scholar 

  • LeBauer DS, Wang D, Richter KT, Davidson CC, Dietze MC (2013) Facilitating feedbacks between field measurements and ecosystem models. Ecol Monogr 83:133–154. doi:10.1890/12-0137.1

    Google Scholar 

  • Mahecha MD, Reichstein M, Lange H, Carvalhais N, Bernhofer C, Grünwald T, Papale D, Seufert G (2007) Characterizing ecosystem-atmosphere interactions from short to interannual time scales. Biogeosciences 4:743–758

    Article  CAS  Google Scholar 

  • Mahecha MD, Reichstein M, Jung M, Seneviratne SI, Zaehle S, Beer C, Braakhekke MC, Carvalhais N, Lange H, Le Maire G, Moors E (2010) Comparing observations and process-based simulations of biosphere-atmosphere exchanges on multiple time scales. J Geophys Res 115:G02003. doi:10.1029/2009JG001016

    Google Scholar 

  • Medvigy D, Wofsy SC, Munger JW, Hollinger DY, Moorcroft PR (2009) Mechanistic scaling of ecosystem function and dynamics in space and time: the Ecosystem Demography model version 2. J Geophys Res 114:G01002. doi:10.1029/2008JG000812

    Google Scholar 

  • Medvigy D, Wofsy SC, Munger JW, Moorcroft PR (2010) Responses of terrestrial ecosystems and carbon budgets to current and future environmental variability. Proc Natl Acad Sci USA 107:8275–8280

    Article  CAS  PubMed  Google Scholar 

  • Moffat AM, Papale D, Reichstein M et al (2007) Comprehensive comparison of gap-filling techniques for eddy covariance net carbon fluxes. Agric For Meteorol 147:209–232. doi:10.1016/j.agrformet.2007.08.011

    Article  Google Scholar 

  • Moorcroft PR (2006) How close are we to a predictive science of the biosphere? Trends Ecol Evol 21:400–407

    Article  PubMed  Google Scholar 

  • Niu S et al (2012) Thermal optimality of net ecosystem exchange of carbon dioxide and underlying mechanisms. New Phytol 194:775–783. doi:10.1111/j.1469-8137.2012.04095.x

    Article  PubMed  Google Scholar 

  • Norby RJ, Zak DR (2011) Ecological lessons from free-air CO2 enrichment (FACE) experiments. Annu Rev Ecol Evol Syst 42:181–203

    Article  Google Scholar 

  • Raupach MR, Rayner PJ, Barrett DJ, DeFries RS, Heimann M, Ojima DS, Quegan S, Schmullius CC (2005) Model-data synthesis in terrestrial carbon observation: methods, data requirements and data uncertainty specifications. Glob Change Biol 11:378–397

    Article  Google Scholar 

  • Ricciuto DM, Butler MP, Davis KJ, Cook BD, Bakwin P, Andrews A, Teclaw RM (2008) Causes of interannual variability in ecosystem-atmosphere CO2 exchange in a northern Wisconsin forest using a Bayesian model calibration. Agric For Meteorol 148:309–327

    Article  Google Scholar 

  • Richardson AR et al (2012) Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis. Glob Change Biol 18:566–584. doi:10.1111/j.1365-2486.2011.02562.x

    Article  Google Scholar 

  • Schaefer K et al (2012) A model-data comparison of gross primary productivity: results from the North American Carbon Program Site Synthesis. J Geophys Res 117:G03010. doi:10.1029/2012JG001960

    Google Scholar 

  • Scheffer M, Carpenter S, Foley JA, Folke C, Walker B (2001) Catastrophic shifts in ecosystems. Nature 413:591–596

    Google Scholar 

  • Sellers PJ (1985) Canopy reflectance, photosynthesis and transpiration. Int J Remote Sens 6:1335–1372. doi:10.1080/01431168508948283

    Article  Google Scholar 

  • Sprintsin M, Chen JM, Desai AR, Gough CM (2012) Evaluation of leaf-to-canopy upscaling methodologies against carbon flux data in North America. J Geophys Res 117:G01023. doi:10.1029/2010JG001407

    Google Scholar 

  • Stoy PC, Richardson AD, Baldocchi DD, Katul GG, Stanovick J, Mahecha MD, Reichstein M, Detto M, Law BE, Wohlfahrt G, Arriga N, Campos J, McCaughey JH, Montagnani L, Paw UKT, Sevanto S, Williams M (2009) Biosphere-atmosphere exchange of CO2 in relation to climate: a cross-biome analysis across multiple time scales. Biogeosciences 6:2297–2312

    Article  CAS  Google Scholar 

  • Van Gorsel E, Delpierre N, Leuning R et al (2009) Estimating nocturnal ecosystem respiration from the vertical turbulence flux and change in storage of CO2. Agric For Meteorol 149:1919–1930. doi:10.1016/j.agrformet.2009.06.020

    Article  Google Scholar 

  • Walter J, Beierkuhnlein C, Jentsch A, Kreyling J (2013) Ecological stress memory and cross stress tolerance in plants in the face of climate extremes. Environ Exp Bot. doi:10.1016/j.envexpbot.2012.02.009

    Google Scholar 

  • Williams M, Richardson AD, Reichstein M, Stoy PC, Peylin P, Verbeeck H, Carvalhais N, Jung M, Hollinger DY, Kattge J, Leuning R, Luo Y, Tomelleri E, Trudinger C, Wang Y-P (2009) Improving land surface models with FLUXNET data. Biogeosciences 6:1341–1359

    Article  CAS  Google Scholar 

  • Wu C, Chen JM, Black TA et al (2013) Interannual variability of net ecosystem productivity in forests is explained by carbon flux phenology in autumn. Glob Ecol Biogeogr. doi:10.1111/geb.12044

    Google Scholar 

  • Yi C, Davis KJ, Bakwin PS, Berger BW, Marr L (2000) The influence of advection on measurements of the net ecosystem-atmosphere exchange of CO2 from a very tall tower. J Geophys Res 105:9991–9999

    Article  CAS  Google Scholar 

  • Yi C, Ricciuto DM, Li R et al (2010) Climate control of terrestrial carbon exchange across biomes and continents. Environ Res Lett 5:034007. doi:10.1088/1748-9326/5/3/034007

    Article  Google Scholar 

  • Zobitz J, Desai AR, Moore DJP, Chadwick MA (2011) A primer for data assimilation with ecological models using Markov Chain Monte Carlo (MCMC). Oecologia 167:599–611. doi:10.1007/s00442-011-2107-9

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

This manuscript would not have been possible with the numerous person-hours of support that going into the making of observations at WLEF including J. Thom at UW-Madison, A. Andrews and J. Kofler at NOAA-ESRL, R. Strand and J. Ayers at State of Wisconsin Educational Communications Board, K. Davis and current/former lab members at The Pennsylvania State University, P. Bolstad at University of Minnesota, and B. Cook at NASA GSFC. I also would like to thank A. Leakey for organizing this special issue. Observations and research were supported through NSF Biology Directorate grants #DEB-0845166 and #DBI-1062204.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ankur R. Desai.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Desai, A.R. Influence and predictive capacity of climate anomalies on daily to decadal extremes in canopy photosynthesis. Photosynth Res 119, 31–47 (2014). https://doi.org/10.1007/s11120-013-9925-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11120-013-9925-z

Keywords

Navigation