Quantifying nutritional trade-offs across multidimensional performance landscapes

Animals make feeding decisions to simultaneously maximise fitness traits that often require different nutrients. Recent quantitative methods have been developed to characterise these nutritional trade-offs from performance landscapes on which traits are mapped on a nutrient space defined by two nutrients. This limitation constrains the broad applications of previous methods to more complex data, and a generalised framework is needed. Here, we build upon previous methods and introduce a generalised vector-based approach – the Vector of Position approach – to study nutritional trade-offs in complex multi-dimensional spaces. The Vector of Position Approach allows the estimate of performance variations across entire landscapes (peaks and valleys), and compare these variations between animals. Using landmark published datasets on lifespan and reproduction landscapes, we illustrate how our approach gives accurate quantifications of nutritional trade-offs in two- and three-dimensional spaces, and can bring new insights into the underlying nutritional differences in trait expression between species. The Vector of Position Approach provides a generalised framework for investigating nutritional differences in life-history traits expression within and between species, an essential step for the development of comparative research on the evolution of animal nutritional strategies.