Joint Multivariate and Functional Modeling for Plant Traits and Reflectances

TL;DR

This paper develops a joint multivariate and functional modeling approach to analyze how plant traits and reflectance spectra depend on environmental factors, using data from South Africa to improve understanding of plant ecology.

Contribution

It introduces a novel joint modeling framework for traits and reflectance spectra conditioned on environmental variables, capturing their dependence along environmental gradients.

Findings

Effective modeling of trait-reflectance dependence

Insights into plant trait responses to environment

Enhanced understanding of plant reflectance spectra

Abstract

The investigation of leaf-level traits in response to varying environmental conditions has immense importance for understanding plant ecology. Remote sensing technology enables measurement of the reflectance of plants to make inferences about underlying traits along environmental gradients. While much focus has been placed on understanding how reflectance and traits are related at the leaf-level, the challenge of modelling the dependence of this relationship along environmental gradients has limited this line of inquiry. Here, we take up the problem of jointly modeling traits and reflectance given environment. Our objective is to assess not only response to environmental regressors but also dependence between trait levels and the reflectance spectrum in the context of this regression. This leads to joint modeling of a response vector of traits with reflectance arising as a functional response over the wavelength spectrum. To conduct this investigation, we employ a dataset from a global biodiversity hotspot, the Greater Cape Floristic Region in South Africa.