American Institute of Mathematical Sciences

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2008, 5(1): 101-124. doi: 10.3934/mbe.2008.5.101

The role of leaf height in plant competition for sunlight: analysis of a canopy partitioning model

Andrew L. Nevai 1, and  Richard R. Vance 2,

1. 

Department of Mathematics, University of California, Los Angeles, CA 90095, United States
2. 

Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, United States

Received  July 2007 Revised  October 2007 Published  January 2008

A global method of nullcline endpoint analysis is employed to de- termine the outcome of competition for sunlight between two hypothetical plant species with clonal growth form that differ solely in the height at which they place their leaves above the ground. This difference in vertical leaf placement, or canopy partitioning, produces species differences in sunlight energy capture and stem metabolic maintenance costs. The competitive interaction between these two species is analyzed by considering a special case of a canopy partitioning model (RR Vance and AL Nevai, J. Theor. Biol. 2007, 245:210-219; AL Nevai and RR Vance, J. Math. Biol. 2007, 55:105-145). Nullcline endpoint analysis is used to partition parameter space into regions within which either competitive exclusion or competitive coexistence occurs. The principal conclu- sion is that two clonal plant species which compete for sunlight and place their leaves at different heights above the ground but differ in no other way can, un- der suitable parameter values, experience stable coexistence even though they occupy an environment which varies neither over horizontal space nor through time.
Keywords: canopy structure model, light competition, plant competi- tion, mathematical model., canopy partitioning model, stable coexistence.
Mathematics Subject Classification: Primary: 92D25; Secondary: 34C23, 34D23, 92C80, 92D4.
Citation: Andrew L. Nevai, Richard R. Vance. The role of leaf height in plant competition for sunlight: analysis of a canopy partitioning model. Mathematical Biosciences & Engineering, 2008, 5 (1) : 101-124. doi: 10.3934/mbe.2008.5.101
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