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Peter J. Grubb

Researcher at University of Cambridge

Publications -  80
Citations -  11667

Peter J. Grubb is an academic researcher from University of Cambridge. The author has contributed to research in topics: Rainforest & Shade tolerance. The author has an hindex of 46, co-authored 80 publications receiving 11155 citations. Previous affiliations of Peter J. Grubb include Kyushu University & Australian National University.

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Trade-offs in interspecific comparisons in plant ecology and how plants overcome proposed constraints

TL;DR: It is demonstrated that statistically significant and ecologically important negative correlations between features A and B in the ‘trend line’ type of plot can be accompanied by huge variation from the trend line, and that authors have not always tested sufficiently rigorously the constraint lines concerning combinations of supposedly incompatible tolerances.
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Morphological plasticity of shade-tolerant tropical rainforest tree seedlings exposed to light changes

TL;DR: In this paper, the authors examined morphological traits in seedlings of 10 shade-tolerant tropical rainforest tree species grown in four combinations of high and low light (10 and 0·8% full daylight, respectively).
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The ecology of very small-seeded shade-tolerant trees and shrubs in lowland rain forest in Singapore

TL;DR: A study was made in Bukit Timah Nature Reserve of niche differentiation among 11 woody species that have very small seeds and establish in deep shade, i.e., where the indirect site factor under cloudy conditions is ≤2%, and one taxonomically related light-demander (seed mass 33 µg).
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Seed mass and nutrient content in nutrient-starved tropical rainforest in Venezuela

TL;DR: The tall trees of caatinga have smaller seeds than the tall trees in adjacent forest on less infertile soil (both overall and in six taxonomically controlled comparisons), and than thetall trees in lowland rainforests elsewhere.
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Evolution of flowering decisions in a stochastic, density-dependent environment

TL;DR: By combining a range of theoretical approaches with the statistical analysis of individually structured databases, accurate prediction of life history decisions is possible in natural density-regulated populations undergoing large fluctuations in demographic rates from year to year.