Unknown

Dataset Information

0

Flow similarity model predicts the allometry and allometric covariation of petiole dimensions.


ABSTRACT: Allometric relationships for plants, plant organs and plant parts, have long generated interest among biologists. Several prominent theoretical models based on biomechanical and/or hydraulic arguments have been introduced with mixed support. Here, I test a more recent offering, flow similarity, which is based on the conservation of volumetric flow rate and velocity. Using dimensional data for 935 petioles from 43 angiosperm species, I show that both the intraspecific and interspecific petiole allometries are more closely aligned with the predictions of the flow similarity model than that of elastic or geometric similarity. Further, allometric covariation among empirical scaling exponents falls along predicted functions with clustering around the flow similarity predictions. This work adds to the body of literature highlighting the importance of hydraulics in understanding the physiological basis of plant allometries, identifies previously unknown central tendencies in petiole allometry, and helps to delineate the scope within which the flow similarity model may be applicable.

SUBMITTER: Price CA 

PROVIDER: S-EPMC10323609 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

altmetric image

Publications

Flow similarity model predicts the allometry and allometric covariation of petiole dimensions.

Price Charles A CA  

Plant direct 20230706 7


Allometric relationships for plants, plant organs and plant parts, have long generated interest among biologists. Several prominent theoretical models based on biomechanical and/or hydraulic arguments have been introduced with mixed support. Here, I test a more recent offering, flow similarity, which is based on the conservation of volumetric flow rate and velocity. Using dimensional data for 935 petioles from 43 angiosperm species, I show that both the intraspecific and interspecific petiole al  ...[more]

Similar Datasets

| S-EPMC1941814 | biostudies-other
| S-EPMC8770586 | biostudies-literature
| S-EPMC10928110 | biostudies-literature
| S-EPMC3760856 | biostudies-literature
| S-EPMC7486732 | biostudies-literature
| S-EPMC10072084 | biostudies-literature
| S-EPMC3465447 | biostudies-literature
| S-EPMC6207370 | biostudies-literature
| S-EPMC6108490 | biostudies-literature
2019-03-08 | GSE121420 | GEO