Modeling the growth of individuals in plant populations: local density variation in a strand population of Xanthium strumarium (Asteraceae)

We studied the growth of individual Xanthium strumarium plants growing at four naturally occurring local densities on a beach in Maine: (1) isolated plants, (2) pairs of plants less than or equal to 1 cm apart, (3) four plants within 4 cm of each other, and (4) discrete dense clumps of 10-39 plants....

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Veröffentlicht in:American journal of botany 1998-11, Vol.85 (11), p.1638-1645
Hauptverfasser: Weiner, Jacob, Kinsman, Sharon, Williams, Sharon
Format: Artikel
Sprache:eng
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Zusammenfassung:We studied the growth of individual Xanthium strumarium plants growing at four naturally occurring local densities on a beach in Maine: (1) isolated plants, (2) pairs of plants less than or equal to 1 cm apart, (3) four plants within 4 cm of each other, and (4) discrete dense clumps of 10-39 plants. A combination of nondestructive measurements every 2 wk and parallel calibration harvests provided very good estimates of the growth in aboveground biomass of over 400 individual plants over 8 wk and afforded the opportunity to fit explicit growth models to 293 of them. There was large individual variation in growth and resultant size within the population and within all densities. Local crowding played a role in determining plant size within the population: there were significant differences in final size between all densities except pairs and quadruples, which were almost identical. Overall, plants growing at higher densities were more variable in growth and final size than plants growing at lower densities, but this was due to increased variation among groups (greater variation in local density and/or greater environmental heterogeneity), not to increased variation within groups. Thus, there was no evidence of size asymmetric competition in this population. The growth of most plants was close to exponential over the study period, but half the plants were slightly better fit by a sigmoidal (logistic) model. The proportion of plants better fit by the logistic model increased with density and with initial plant size. The use of explicit growth models over several growth intervals to describe stand development can provide more biological content and more statistical power than "growth-size" methods that analyze growth intervals separately
ISSN:0002-9122
1537-2197
DOI:10.2307/2446493