Authors: Tao, Ye
Zhang, Ming
Title: Plant traits with different dimensions of shrubs represent different spatial patterns and plant-to-plant interactions in a temperate desert
Language (ISO): en
Abstract: Projective cover (PC) and aboveground biomass (AGB) are the key traits with space attributes of individual plants. They are crucial to the understanding of the plant dynamics and plant patterns at population level. Spatial patterns based on individual plant positions (IND) have been extensively investigated in previous studies. However, very few have focused on PC and AGB. We tested the hypothesis that different plant traits represent different spatial patterns and plant-to-plant interactions. Two 40 m × 40 m plots of two typical desert shrub populations (Seriphidium terrae-albae and Artemisia songarica) were surveyed in the Gurbantunggut Desert of north-western China. Each plot was divided into a series of subplots (grids) at different scales (17 scales from 0.5 m to 20 m) using GIS (geographic information system). The spatial patterns of IND, PC and AGB were determined using aggregation and information dimension analyses together with changes in the scales. The IND and AGB of the two populations exhibited clumped tendencies at all scales (except at the 0.5 m scale for S. terrae-albae), whereas PC showed uniform distribution patterns at the moderate and small scales, (0.5 m to 8.0 m for S. terrae-albae and 0.5 m to 4.0 m for A. songarica), indicating that crown-to-crown competition for sunlight was strong at these scales. Although IND had a slightly higher coefficient of variation at the small scales, its information dimension was smaller than those of PC and AGB, indicating that PC and AGB had higher spatial complexities. In conclusion, the three parameters represented different spatial patterns across multiple scales; PC and AGB showed strong spatial complexities and PC was also an accurate indicator of plant-to-plant competition.
Subject Headings: spatial complexity
rojective cover
biomass
information dimension
aggregation analysis
plant location
URI: http://hdl.handle.net/2003/32949
http://dx.doi.org/10.17877/DE290R-7475
Issue Date: 2013-07-19
Appears in Collections:Original Articles

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