Back

Plasticity in plant populations may be constrained by performance costs, complex environments and weakly integrated phenotypes

Hennion, F.; Labarrere, B.; Renaudon, M.; Prinzing, A.

2023-09-03 evolutionary biology
10.1101/2023.08.31.555735 bioRxiv
Show abstract

O_LIBackground and Aims One response of plants to climate warming is plasticity of traits, but plasticity might come at a cost and might be limited by the integration among traits or by simultaneous shift of another environmental condition such as shading. Empirical studies treating simultaneously such costs and limitations of plasticity across populations or maternal lineages within species, and how they depend on the environmental context remain few. C_LIO_LIMethods We studied three plant species from the sub-Antarctic, a region currently facing one of the fastest warming worldwide. For multiple populations or maternal lineages we identified (i) plasticity by exposing seeds from a given source population to different temperature and light treatments, (ii) performance (photosynthesis or morphological performance) and (iii) morphological integration of traits in young plants. C_LIO_LIKey Results We found that plants from more plastic source populations performed poorly. Plants from more integrated source populations were more plastic. Exposure to shade rendered plants less plastic to a warming trend. Moreover, simultaneous shading and warming, rather than sole shading or sole warming, reduced plant performance. C_LIO_LIConclusions Our results suggest that phenotypic integration of intraspecific lineages surprisingly might favour rather than limit plasticity. However, our results also suggest that plasticity in response to climate warming may be limited by parallel increase in shading from other plants including competitors, and itself does not ensure success due to induced performance costs. C_LI

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.