How can crop modeling and plant physiology help to understand the plant responses to climate change? A case study with sugarcane

Abstract

Global climate changes are now well accepted to happen and can likely impact agriculture. Process-based dynamic crop models are able to estimate a range of crop responses to the environment and to assess the biophysical effects of future climate scenarios on crop growth and yield. They are hence scientifically accepted as a predictor of future agricultural scenarios, and the multi-model approach has shown the best performance in such prediction activities. The need of several models for such studies is mainly a consequence of the different physiological and physical approaches applied by model developers. Physiological processes are in fact essential elements for improving plant modeling, and most of the model weakness would be overcome by better understanding of the main physiological aspects related to plant growth and development. Sugarcane (Saccharum spp.) is an important crop for coping with climate change mitigation as a source of bioenergy and food. In this paper we aim to demonstrate how important is plant physiology for advancing the process-based crop models by briefly reviewing the history of the modeling along the last five decades and presenting the key physiological process considered in crop models. The paper was based in the DSSAT/CANEGRO sugarcane model and a set of field experiments for exemplifying some model responses to key climatic variables expected to vary in the following decades. Those responses were discussed under the light of plant physiology knowledge. We selected two sites in the State of Sao Paulo for an exercise of local sensitivity analysis. As air CO2 concentration is the most likely environmental variable expected to change, we stressed the CO2 effects on plant photosynthesis and water use to highlight the model strengths and opportunities for model improvements based on plant physiology findings.