Is Temporal Variation of Soil Respiration Linked to the Phenology of Photosynthesis?



If recent photosynthate is the primary source of carbohydrates for root respiration and possibly for much of soil microbial respiration through root exudates, then temporal variation in soil respiration (SR) may be linked to plant phenological patterns at hourly to seasonal time scales. Here we review the evidence for this linkage and identify the research needs for improving our understanding of the physiological and ecological linkages between photosynthesis and respiration in ecosystems. The linkage is clearest at the season time scale, where the importance of substrate supply to belowground carbon processes follows a seasonal pattern in temperate and boreal ecosystems. Correlations of SR with canopy light, temperature, and vapor pressure deficit also suggest a link between root respiration and canopy photosynthesis on times scales of a few hours to about 3 weeks. Temporal correlations between photosynthetic activity and SR make it tempting to view patterns in SR as the direct outcome of variation in substrate delivery rates, but these analyses provide only inferential evidence of a physiological linkage. Isotopic labeling studies indicate that the lag between fixation by foliage and respiration of the label in the rhizosphere is usually on the order of a day or more in forest ecosystems. More rapid transmission of pressure/concentration waves through the phloem is theoretically possible, and current understanding of phloem physiology and the regulation of growth suggests that the linkage between canopy and root processes is based on more than the mass transport of substrate from sources to sinks. However, improved understanding of assimilate transport and partitioning is needed before variation in SR patterns can be linked mechanistically to the physiology and the phenology of the plants fueling belowground metabolism.


Soil Respiration Vapor Pressure Deficit Root Respiration Canopy Photosynthesis Diel Variation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This research was supported by the U.S. Department of Energy’s Office of Science (BER) through Grant Nos. DE-FG02–00ER63002 and 07-DG-11242300–091 and through the Northeastern Regional Center of the National Institute for Climatic Change Research, Grant No. DE-FC02–06ER64157.


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.The Woods Hole Research CenterWoods HoleUSA
  2. 2.Department of Organismic and Evolutionary BiologyHarvard UniversityCambridgeUSA

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