ArticlePlant signaling & behavior2021
Future paths for the 'exploitative segregation of plant roots' model.
Article in Plant signaling & behavior, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Root tragedy of the commons: Revisiting the mechanisms of a misunderstood theory.Frontiers in plant science · 2022Article
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Authors and funding
5 authors.
Funding
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Abstract
The exploitative segregation of plant roots (ESPR) is a theory that uses a game-theoretical model to predict plant root foraging behavior in space. The original model returns the optimal root distribution assuming exploitative competition between a pair of identical plants in soils with homogeneous resource dynamics. In this short communication, we explore avenues to develop this model further. We discuss: (i) the response of single plants to soil heterogeneity; (ii) the variability of the plant response under uneven competition scenarios; (iii) the importance of accounting for the constraints and limitations to root growth that may be imposed from the plant shoot; (iv) the importance of root functional traits to predict root foraging behavior; (v) potential model extensions to investigate facilitation by incorporating facilitative traits to roots, and (vi) the possibility of allowing plants to tune their response by accounting for non-self and non-kin root recognition. For each case, we introduce the topic briefly and present possible ways to encode those ingredients in the mathematical equations of the ESPR model, providing preliminary results when possible.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.