Modelling olive trees and grapevines in a changing climate. (October 2015)

• Record Type: Journal Article
• Authors: Moriondo, Marco; Ferrise, Roberto; Trombi, Giacomo; Brilli, Lorenzo; Dibari, Camilla; Bindi, Marco
• Is Part Of: Environmental modelling & software. Volume 72(2015:Oct.)
• Page Start: 387
• Page End: 401
• Publication Date: 2015-10
• Subjects: Tree crops -- Climate change -- Simulation models -- Crop yield; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2014.12.016
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The models developed for simulating olive tree and grapevine yields were reviewed by focussing on the major limitations of these models for their application in a changing climate. Empirical models, which exploit the statistical relationship between climate and yield, and process based models, where crop behaviour is defined by a range of relationships describing the main plant processes, were considered. The results highlighted that the application of empirical models to future climatic conditions (i.e. future climate scenarios) is unreliable since important statistical approaches and predictors are still lacking. While process-based models have the potential for application in climate-change impact assessments, our analysis demonstrated how the simulation of many processes affected by warmer and CO2 -enriched conditions may give rise to important biases. Conversely, some crop model improvements could be applied at this stage since specific sub-models accounting for the effect of elevated temperatures and CO2 concentration were already developed. Highlights: Empirical models are generally unreliable for their possible application in a changing climate. Complex process-based models have already the potential to provide reliable simulations for a changing climate. There is a clear need to improve the simulation of crop processes in response to increased CO2 and higher temperatures. Process-based models should be improved to simulate soil biochemical processes.