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Open AccessJournal ArticleDOI

The genesis of size hierarchies in seedling populations of impatiens capensis meerb.

D. M. Wallre
- 01 Jun 1985 - 
- Vol. 100, Iss: 2, pp 243-260
TLDR
In this article, the authors used path analysis to summarize the interactions among the continuous variables and to disentangle direct from indirect causal effects, concluding that seed weight enhanced performance primarily through its effects on emergence date and cotyledon area.
Abstract
Summary In 1978 and 1980 I planted 660 and 900 seeds of Impatiens capensis Meerb. at four densities in the greenhouse to examine how variation in plant performance is generated. I noted seed weight, seed type (cleistogamous or chasmogamous), maternal parent, and population of origin, and monitored emergence date, cotyledon area, the biomass of competitors within the same flat, and the final size reached by the seedlings after 63 to 80 d of growth. Larger seeds tended to germinate sooner, as did seeds derived from chasmogamous flowers. Seeds from northern populations took longer to germinate. Seeds from different maternal parents also germinated at different rates. Cotyledon area strongly depended on seed weight, and, to a lesser extent, germination date. Maternal parent and seed type significantly affected cotyledon area in 1980. Plant density and cotyledon area influenced final size the most, but almost every factor proved to be statistically significant. As expected, earlier emerging seedlings with larger cotyledons growing at the lowest density grew into the largest plants. I applied path analysis to summarize the interactions among the continuous variables and to disentangle direct from indirect causal effects. This technique revealed that seed weight enhanced performance primarily through its effects on emergence date and cotyledon area. Chasmogamous seedlings outperformed cleistogamous seedlings, and their advantage was expressed during most phases of growth. Together, the predictor variables accounted for over four-fifths of the total variation in final size. The inequality of plant sizes, as measured by the Gini coefficient, increased appreciably during the course of the experiment. There was no simple relation to density, however, suggesting that both intrinsic differences in growth rate, and competitive dominance and supression fuel the establishment of size hierarchies.

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Citations
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Increased probability of extinction due to decreased genetic effective population size: experimental populations of clarkia pulchella.

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Effect of seed passage through vertebrate frugivores' guts on germination: A review

TL;DR: The hypothesis that enhanced germination may be more advantageous in unpredictable or less constant environments is supported.
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Do Plant Populations Purge Their Genetic Load? Effects of Population Size and Mating History on Inbreeding Depression

TL;DR: Regression analyses suggest that purging is most likely to ameliorate ID for early traits, but these declines are typically modest (5–10%).
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Reproductive Allocation in Plants

TL;DR: This work states that sex-Specific Physiology and its Implications for the Cost of Reproduction are likely to be different for females and males and for males and females respectively.
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Enhancement of inbreeding depression by dominance and suppression in Impatiens capensis

TL;DR: Plant density may influence patterns of natural selection both on mating system and on juvenile traits in natural Impatiens populations, indicating that larger plants competitively suppressed smaller plants in the high‐density treatments.
References
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Book

Population Biology of Plants

Journal ArticleDOI

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Book

On Economic Inequality

TL;DR: In this paper, Amartya Sen relates the theory of welfare economics to the study of economic inequality and presents a systematic treatment of the conceptual framework as well as the practical problems of measurement of inequality.
Journal ArticleDOI

Correlation and Causation

TL;DR: Causality is the area of statistics that is most commonly misused, and misinterpreted, by nonspecialists as discussed by the authors, who fail to understand that, just because results show a correlation, there is no proof of an underlying causality.