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Know thy neighbor
created · Updated
Deadline: Oct 31, 2023
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Summary

Understanding the social networks of plants is essential for predicting their coexistence. For decades, intraspecific interactions were assumed to be purely competitive in nature. However, recent experimental evidence has demonstrated the existence of positive interactions for...

Description

Understanding the social networks of plants is essential for predicting their coexistence. For decades, intraspecific interactions were assumed to be purely competitive in nature. However, recent experimental evidence has demonstrated the existence of positive interactions for various wild plant species, wherein a genotype can recognize a conspecific, and cooperate to reduce competitive growth when growing with either their kin, or even an unrelated intra/con specific. My PhD research took this a step further by giving the first-ever evidence for the existence of both these types of positive interactions within the same plant species, varying between natural populations.<br/><br/>To alter their competitive response, plants must have mechanisms to reliably distinguish the identity of their neighbors. The root systems are known to be critical for sensing and integrating signals that allow plants to perform elaborate behaviors similar to those of intelligent animals. Yet, the underlying mechanisms remain largely unknown. This project aims to understand the direct or indirect role of root-secreted compounds in mediating neighbor perception and recognition in conspecific interactions. To do this, we will combine interdisciplinary approach at the interface of evolutionary ecology, chemistry, quantitative genetics, and microbiology <br/><br/>Understanding how plants recognize each other is a crucial step in determining how competitive traits evolve in intraspecific plant-plant interacting systems, which has implications in both natural and agroecological contexts. Comprehending intraspecific recognition mechanisms can ultimately help illuminate the dynamics of natural plant populations and aid in predicting their resilience in the face of current and future global changes. More importantly, understanding this link between recognition and belowground plastic responses can be exploited to design efficient crop variety mixtures with high yield potential owing to cooperative interactions.

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