Cargando…

Allometric Trajectories and “Stress”: A Quantitative Approach

The term “stress” is an important but vague term in plant biology. We show situations in which thinking in terms of “stress” is profitably replaced by quantifying distance from functionally optimal scaling relationships between plant parts. These relationships include, for example, the often-cited o...

Descripción completa

Detalles Bibliográficos
Autores principales: Anfodillo, Tommaso, Petit, Giai, Sterck, Frank, Lechthaler, Silvia, Olson, Mark E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5101416/
https://www.ncbi.nlm.nih.gov/pubmed/27881990
http://dx.doi.org/10.3389/fpls.2016.01681
Descripción
Sumario:The term “stress” is an important but vague term in plant biology. We show situations in which thinking in terms of “stress” is profitably replaced by quantifying distance from functionally optimal scaling relationships between plant parts. These relationships include, for example, the often-cited one between leaf area and sapwood area, which presumably reflects mutual dependence between sources and sink tissues and which scales positively within individuals and across species. These relationships seem to be so basic to plant functioning that they are favored by selection across nearly all plant lineages. Within a species or population, individuals that are far from the common scaling patterns are thus expected to perform negatively. For instance, “too little” leaf area (e.g., due to herbivory or disease) per unit of active stem mass would be expected to incur to low carbon income per respiratory cost and thus lead to lower growth. We present a framework that allows quantitative study of phenomena traditionally assigned to “stress,” without need for recourse to this term. Our approach contrasts with traditional approaches for studying “stress,” e.g., revealing that small “stressed” plants likely are in fact well suited to local conditions. We thus offer a quantitative perspective to the study of phenomena often referred to under such terms as “stress,” plasticity, adaptation, and acclimation.