Acclimation of the to respiration/photosynthesis raio to temperature insights from a model

Roderick C. Dfwar*, Belinda E. Medlyxt, Ross E. McMurtrieij

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

215 Citations (Scopus)

Abstract

Abstract Based on short-term experiments, many plant growth models - including those used in global change research - assume that an increase in temperature stimulates plant respiration (R) more than photosynthesis (P), leading to an increase in the TUP ratio. Longer-term experiments, however, have demonstrated that RIP is relatively insensitive to growth temperature. We show that both types of temperature response may be reconciled within a simple substrate-based model of plant acclimation to temperature, in which respiration is effectively limited by the supply of carbohydrates fixed through photosynthesis. The short-term, positive temperature response of RIP reflects the transient dynamics of the nonstructural carbohydrate and protein pools; the insensitivity of RIP to temperature on longer time-scales reflects the steady-state behaviour of these pools. Thus the substrate approach may provide a basis for predicting plant respiration responses to temperature that is more robust than the current modelling paradigm based on the extrapolation of results from short-term experiments. The present model predicts that the acclimated RIP depends mainly on the internal allocation of carbohydrates to protein synthesis, a better understanding of which is therefore required to underpin the wider use of a constant RIP as an alternative modelling paradigm in global change research.

Original languageEnglish
Pages (from-to)615-622
Number of pages8
JournalGlobal Change Biology
Volume5
Issue number5
Publication statusPublished - 1999
Externally publishedYes

Keywords

  • Acclimation
  • Model
  • Photosynthesis
  • Respiration
  • Temperature

Fingerprint

Dive into the research topics of 'Acclimation of the to respiration/photosynthesis raio to temperature insights from a model'. Together they form a unique fingerprint.

Cite this