📝 SummarXiv

Abstract

Photosynthesis-irradiance (PI) curves are foundational for quantifying primary production, parameterizing ecosystem and biogeochemical models, and interpreting physiological acclimation to light. Despite their broad use, researchers lack a unified, reproducible toolkit to fit, compare, and diagnose the many PI formulations that have accumulated over the last century. We introduce piCurve, an R package that standardizes the modeling of PI relationships, with a library of widely used light-limited, light-saturated, and photoinhibited formulations and a consistent statistical framework for estimation and comparison. With the total of 24 PI models, piCurve supports mean squared error (MSE) and maximum likelihood estimation (MLE), provides uncertainty quantification via information matrix (Hessian), and includes automated, data-informed initialization to improve convergence. Utilities classify PI data into light-limited, light-saturated, and photoinhibited regions, while plotting and 'tidy' helpers streamline workflow and reporting. Together, these features enable reproducible analyses and fair model comparisons, including for curves exhibiting a plateau followed by photoinhibition.