
Bases conceptuales y herramientas gráficas para investigar cómo funcionan los rasgos funcionales
Author(s) -
Andrés G. Rolhauser
Publication year - 2022
Publication title -
darwiniana
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.31
H-Index - 21
eISSN - 1850-1699
pISSN - 0011-6793
DOI - 10.14522/darwiniana.2022.101.1000
Subject(s) - trait , fitness landscape , niche , biology , population , function (biology) , ecology , evolutionary biology , computer science , sociology , demography , programming language
Functional traits constitute a promising research avenue to explain and predict ecological patterns at different levels of organization (genotypes, populations, communities) because they link individual responses to environmental conditions. However, Argentine ecologists and botanists seem not to have explored this line of research as much as colleagues in other parts of the world. With this work I intend to promote the use of functional traits among local and regional readers. Amalgamating often conflicting definitions proposed by other authors, I define functional traits as morphological characteristics that affect a chain of physiological and ecological processes that I refer to as function, vital rate, and population fitness. The purpose of this definition is to emphasize the mechanistic relationship between plant structure and function. The practical benefits are straightforward: predicting the future of a plant or a group of plants from their physical properties, which are generally easier to obtain than physiological or phenological measures. Next, I use two types of graphical tools to discuss the functionality of four key traits: potential plant height, seed mass, leaf mass per area, and leaf size. These graphical tools are (i) path diagrams that show direct or indirect, positive or negative connections between traits and fitness and (ii) cartesian graphs that describe the functional relationships between traits and vital rates that, when combined, result in optimum trait–fitness relationships. Theory indicates that such optimum relationships would be the norm rather than the exception, even though functional traits are generally interpreted as “indicators” of plant functions, which exclusively implies linear relationships. These graphical tools may help us produce predictions that guide data generation and contribute to fill important information gaps regarding the mechanistic link between plant form and population fitness. Although functional traits alone are unlikely to offer complete explanations or infallible predictions, ignoring them would deny us an irreplaceable source of information to understand and predict plant population and community responses to environmental conditions in a changing world.