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C4 Pathway and CAM01:27

C4 Pathway and CAM

Most plants use the C3 pathway for carbon fixation. However, some plants, such as sugar cane, corn, and cacti that grow in hot conditions, use alternative pathways to fix carbon and conserve energy loss due to photorespiration. Photorespiration is the process that occurs when the oxygen concentration is high. Under such conditions, the rubisco enzyme in the Calvin cycle binds O2 instead of CO2, which halts photosynthesis and consumes energy.
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Related Experiment Video

Updated: May 25, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

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Published on: July 3, 2020

Modeling carbon allocation in trees: a search for principles.

Oskar Franklin1, Jacob Johansson, Roderick C Dewar

  • 1IIASA, International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria. franklin@iiasa.ac.at

Tree Physiology
|January 27, 2012
PubMed
Summary
This summary is machine-generated.

Predicting forest carbon and nitrogen allocation requires advanced models. Evolution-based approaches, like adaptive dynamics, offer superior insights into environmental variability and climate change impacts compared to simpler methods.

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Published on: October 16, 2018

Area of Science:

  • Forest Ecology
  • Ecosystem Modeling
  • Evolutionary Biology

Background:

  • Accurate prediction of carbon and nitrogen allocation in forests is crucial for understanding ecosystem responses to environmental change.
  • Existing models vary in complexity, from simple empirical methods to sophisticated evolution-based approaches.

Purpose of the Study:

  • To review and compare different approaches for predicting carbon and nitrogen allocation in forest models.
  • To evaluate the strengths and limitations of empirical, allometric, and evolution-based methods.
  • To discuss the potential of adaptive dynamics and entropy-based methods for future model development.

Main Methods:

  • Review of existing literature on forest carbon and nitrogen allocation models.
  • Comparison of assumptions, strengths, and limitations of empirical, allometric, optimal response (OR), game-theoretical optimization (GTO), adaptive dynamics (AD), and entropy-based approaches.
  • Analysis of model predictions under specific competitive conditions, including free-air carbon dioxide enrichment (FACE) experiments.

Main Results:

  • Empirical and allometric methods are computationally efficient but limited in explaining complex environmental effects.
  • Evolution-based methods, particularly OR and GTO, better capture multifaceted environmental variability and climate change impacts.
  • OR models can predict allocation under single-resource competition, while GTO accounts for multidimensional competition.
  • OR models showed similar predictions to GTO models under root-competitive conditions observed in FACE experiments.
  • Adaptive dynamics (AD) represents a more evolutionarily realistic approach by considering eco-evolutionary dynamics.

Conclusions:

  • Evolution-based models offer greater predictive power for forest carbon and nitrogen allocation under changing environmental conditions.
  • Adaptive dynamics and entropy-based approaches represent promising future directions for allocation modeling.
  • Enhanced datasets, like FLUXNET, coupled with ancillary measurements (water, soil nitrogen), are vital for advancing model development.