Skip to main content
SpringerLink
Log in

Structural and Functional Analyses of Bryophyte Canopies

  • Chapter
  • First Online:
Photosynthesis in Bryophytes and Early Land Plants

Part of the book series: Advances in Photosynthesis and Respiration ((AIPH,volume 37))

Summary

Although not often discrete, the canopy (i.e., the organization of branches, shoot systems and their extent) remains the most definable and useful unit of function in bryophytes. Chambers used for gas exchange provide an integrated summary of canopy photosynthetic function. However, other techniques can provide more information on spatial variation in physiological process in both the horizontal and vertical planes. Three examples of such studies are presented here. First, variation in photosystem II (PSII) function has been evaluated, along a canopy surface, using an imaging chlorophyll fluorometer. We evaluated the quantum yield of PSII, ϕPSII, and calculated the relative rate of photosynthetic electron transport (RETR) on 7 cm diameter samples of ten Sphagnum species during drying. Spatial variation in RETR increased both during drying as well as in high light, which led to different relationships between mean RETR and its variation—across light gradients, the relationship was positive, but negative when RETR was reduced by tissue desiccation. Studies of photosynthetic function using chlorophyll fluorescence measurements need to match their sampling protocols to account for this difference. Further, combining a laser scanning approach that provides three-dimensional information on canopy structure with functional imaging allows assessment of function in three dimensions (3D) within the canopy. This is illustrated using a thermal imaging camera to measure temperature distribution within Pleurozium schreberi canopies under still conditions and with wind. This imaging system resolved 9 °C temperature differences within the canopy and localized shoot temperature relative to canopy height. Finally, computational canopy (i.e., virtual) models have been developed for bryophyte canopies, particularly ones with simple branching structure. A model of this type is shown here for the liverwort Bazzania trilobata and a light model implemented using a ray tracing algorithm. Output from this model followed the attenuation of light predicted by the Lambert-Beer Law and such a technique can be used to evaluate how branching architecture and density affect the dynamics of light capture in bryophytes. New approaches based on novel imaging technologies are in rapid development and present opportunities to further our understanding of function within bryophyte canopies.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Abbreviations

Chl –:

Chlorophyll;

ETR –:

Rate of photosynthetic electron transport as calculated from chlorophyll a fluorescence measurements;

F0 :

– Baseline fluorescence in dark-adapted tissue;

F0’:

– Baseline fluorescence in light-adapted tissue;

Fm :

– Maximum chlorophyll a fluorescence in dark-adapted tissue at saturating light;

Fv/Fm :

– Ratio of variable (=Fm − Fo) to maximal fluorescence in dark-adapted tissue;

Fv’/Fm’:

– Ratio of variable to maximal fluorescence in light-adapted tissue;

I0 :

– Intensity of incident light at top of canopy;

Ix :

– Intensity of incident light at depth x within canopy;

K:

– Light extinction coefficient;

Kapp :

– Apparent light extinction coefficient, product of K and SAIx;

PPFD:

– Photosynthetic photon flux density;

PRI:

– Photochemical reflectance index;

Q10 :

– Temperature coefficient;

RETR:

– Relative rate of (calculated) photosynthetic electron transport;

SAIx :

– Shoot area index above depth x within canopy;

ϕPSII :

– Quantum yield of photosynthesis as calculated from chlorophyll a fluorescence parameters

References

  • Abramoff MD, Magalhaes PJ, Ram SJ (2004) Image processing with image. J Biophotonics Int 11:36–42

    Google Scholar 

  • Aldea M, Frank TD, DeLucia EH (2006) A method for quantitative analysis of spatially variable physiological processes across leaf surfaces. Photosynth Res 90:161–172

    Article  PubMed  CAS  Google Scholar 

  • Baker NR (2008) Chlorophyll fluorescence: a probe of photosynthesis in vivo. Annu Rev Plant Biol 59:89–113

    Article  PubMed  CAS  Google Scholar 

  • Chaerle L, Leinonen I, Jones HG, Van Der Straeten D (2007) Monitoring and screening plant populations with combined thermal and chlorophyll fluorescence imaging. J Exp Bot 58:773–784

    Article  PubMed  CAS  Google Scholar 

  • Chelle M, Andrieu B (1998) The nested radiosity model for the distribution of light within plant canopies. Ecol Model 111:75–91

    Article  Google Scholar 

  • Davey MC, Ellis-Evans JC (1996) The influence of water content on the light climate within Antarctic mosses characterized using an optical microprobe. J Bryol 19:235–242

    Google Scholar 

  • Davey MC, Rothery P (1997) Interspecific variation in respiratory and photosynthetic parameters in Antarctic bryophytes. New Phytol 137:231–240

    Article  Google Scholar 

  • Gamon JA, Serrano L, Surfus JS (1997) The photochemical reflectance index: an optical indicator of photosynthetic radiation use efficiency across species, functional types, and nutrient level. Oecologia 112:492–501

    Article  Google Scholar 

  • Gerdol R, Bonora A, Poli F (1994) The vertical pattern of pigment concentrations in chloroplasts of Sphagnum capillifolium. Bryologist 97:158–161

    Article  CAS  Google Scholar 

  • Govindjee (2004) Chlorophyll a fluorescence: a bit of basics and history. In: Papageorgiou GC, Govindjee (eds) Chlorophyll a fluorescence: a signature of photosynthesis, vol 19, Advances in photosynthesis and respiration. Springer, Dordrecht, pp 1–42

    Chapter  Google Scholar 

  • Graham EA, Hamilton MP, Mishler BD, Rundel PW, Hansen MH (2006) Use of a networked digital camera to estimate net CO2 uptake of a desiccation-tolerant moss. Int J Plant Sci 167:751–758

    Article  CAS  Google Scholar 

  • Harris A (2008) Spectral reflectance and photosynthetic properties of Sphagnum mosses exposed to progressive drought. Ecohydrology 1:35–42

    Article  CAS  Google Scholar 

  • Hayward PM, Clymo RS (1982) Profiles of water content and pore size in Sphagnum and peat, and their relation to peat bog ecology. Proc Roy Soc Lond B Biol 215:299–325

    Article  Google Scholar 

  • Leinonen I, Jones HG (2004) Combining thermal and visible imagery for estimating canopy temperature and identifying plant stress. J Exp Bot 55:1423–1431

    Article  PubMed  CAS  Google Scholar 

  • Lovelock CE, Robinson SA (2002) Surface reflectance properties of Antarctic moss and their relationship to plant species, pigment composition, and photosynthetic function. Plant Cell Environ 25:1239–1250

    Article  Google Scholar 

  • Maxwell K, Johnson GN (2000) Chlorophyll fluorescence—a practical guide. J Exp Bot 51:659–668

    Article  PubMed  CAS  Google Scholar 

  • Morison JIL, Lawson T (2007) Does lateral gas diffusion in leaves matter? Plant Cell Environ 30:1072–1085

    Article  PubMed  CAS  Google Scholar 

  • Ollinger SV (2011) Sources of variability in canopy reflectance and the convergent properties of plants. New Phytol 189:375–394

    Article  PubMed  CAS  Google Scholar 

  • Oxborough K (2004) Using chlorophyll a fluorescence imaging to monitor photosynthetic performance. In: Papageorgiou GC, Govindjee (eds) Chlorophyll a fluorescence: a signature of photosynthesis, vol 19, Advances in photosynthesis and respiration. Springer, Dordrecht, pp 409–428

    Chapter  Google Scholar 

  • Papageorgiou GC, Govindjee (eds) (2004) Chlorophyll a fluorescence: a signature of photosynthesis, vol 19, Advances in photosynthesis and respiration. Springer, Dordrecht, 818 pages

    Google Scholar 

  • Papageorgiou GC, Govindjee (2011) Photosystem II fluorescence: slow changes – scaling from the past. J Photochem Photobiol B Biol 104:258–270

    Article  CAS  Google Scholar 

  • Pradal C, Dufour-Kowalski S, Boudon F, Fournier C, Godin C (2008) OpenAlea: a visual programming and component-based software platform for plant modeling. Funct Plant Biol 25:751–760

    Article  Google Scholar 

  • Prusinkiewicz P (2000) Simulation modeling of plants and plant ecosystems. Commun ACM 43:84–93

    Article  Google Scholar 

  • Prusinkiewicz P, Lindenmayer A (1990) The algorithmic beauty of plants. Springer, New York

    Book  Google Scholar 

  • Rice SK (2012) The cost of capillary integration for bryophyte canopy water and carbon dynamics. Lindbergia 35:53–62

    Google Scholar 

  • Rice SK, Gutman C, Krouglicof N (2005) Laser scanning reveals bryophyte canopy structure. New Phytol 166:695–704

    Article  PubMed  Google Scholar 

  • Rice SK, Aclander L, Hanson DT (2008) Do bryophyte shoot systems function like vascular plant leaves or canopies? Functional trait relationships in Sphagnum mosses (Sphagnaceae). Am J Bot 95:1366–1374

    Article  PubMed  Google Scholar 

  • Rice SK, Neal N, Mango J, Black K (2011a) Modeling bryophyte productivity across gradients of water availability using canopy form-function relationships. In: Tuba Z, Slack NG, Stark LR (eds) Bryophyte ecology and global change. Cambridge University Press, Cambridge, pp 441–457

    Google Scholar 

  • Rice SK, Neal N, Mango J, Black K (2011b) Relationships among shoot tissue, canopy and photosynthetic characteristics in the feathermoss Pleurozium schreberi. Bryologist 114:367–378

    Article  Google Scholar 

  • Rolfe SA, Scholes JD (2010) Chlorophyll fluorescence imaging of plant-pathogen interactions. Protoplasma 247:163–175

    Article  PubMed  CAS  Google Scholar 

  • Soler C, Sillion F, Blaise F, Dereffye P (2003) An efficient instantiation algorithm for simulating radiant energy transfer in plant models. ACM T Graphic 22:204–233

    Article  Google Scholar 

  • Thévenaz P, Ruttimann UE, Unser M (1998) A pyramid approach to subpixel registration based on intensity. IEEE T Image Process 7:27–41

    Article  Google Scholar 

  • Tobias M, Niinemets Ü (2010) Acclimation of photosynthetic characteristics of the moss Pleurozium schreberi to among-habitat and within-canopy light gradients. Plant Biol 12:743–754

    Article  PubMed  CAS  Google Scholar 

  • Uchida M, Muraoka H, Nakatsubo T, Bekku Y, Ueno T, Kanda H, Koizumi H (2002) Net photosynthesis, respiration, and production of the moss Sanionia uncinata on a glacier foreland in the high Arctic, Ny-Ålesund, Svalbard. Arct Antarct Alp Res 34:287–292

    Article  Google Scholar 

  • Van der Hoeven EC, Huynen CIJ, During HJ (1993) Vertical profiles of biomass, light intercepting area and light intensity in chalk grassland mosses. J Hattori Bot Lab 74:261–270

    Google Scholar 

  • Zona D, Oechel WC, Richards JH, Hastings S, Kopetz I, Ikawa H, Oberbauer S (2011) Light-stress avoidance mechanisms in a Sphagnum-dominated wet coastal Arctic tundra ecosystem in Alaska. Ecology 92:633–644

    Article  PubMed  CAS  Google Scholar 

  • Zotz G, Kahler H (2007) A moss “canopy” – Small-scale differences in microclimate and physiological traits in Tortula ruralis. Flora 202:661–666

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank James Ross for conducting preliminary studies using 3D thermography, Mark Hooker, Kristina Streignitz for technical assistance. SKR thanks the Union College for sabbatical leave that facilitated writing of this chapter.

Author information

Authors and Affiliations

  1. Department of Biological Sciences, Union College, Schenectady, NY, 12308, USA

    Steven K. Rice

  2. Department of Biology, University of New Mexico, Albuquerque, NM, 87131, USA

    David T. Hanson

  3. Department of Biology, Utah State University, Logan, UT, 84322, USA

    Zach Portman

Authors
  1. Steven K. Rice
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. David T. Hanson
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zach Portman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Steven K. Rice .

Editor information

Editors and Affiliations

  1. Department of Biology, University of New Mexico, Albuquerque, New Mexico, USA

    David T. Hanson

  2. Department of Biological Sciences, Union College, Schenectady, New York, USA

    Steven K. Rice

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Rice, S.K., Hanson, D.T., Portman, Z. (2014). Structural and Functional Analyses of Bryophyte Canopies. In: Hanson, D., Rice, S. (eds) Photosynthesis in Bryophytes and Early Land Plants. Advances in Photosynthesis and Respiration, vol 37. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6988-5_10

Download citation

Publish with us

Policies and ethics

Search

Navigation