Modelling pasture production and soil temperature, water and carbon fluxes in Mediterranean grassland systems with the Pasture Simulation model

Abstract

Grasslands play important roles in agricultural production and provide a range of ecosystem services. Modelling can be a valuable adjunct to experimental research in order to improve the knowledge and assess the impact of management practices in grassland systems. In this study, the PaSim model was assessed for its ability to simulate plant biomass production, soil temperature, water content, and total and heterotrophic soil respiration in Mediterranean grasslands. The study site was the extensively managed sheep grazing system at the Berchidda‐Monti Observatory (Sardinia, Italy), from which two data sets were derived for model calibration and validation respectively. A new model parameterization was derived for Mediterranean conditions from a set of eco‐physiological parameters. With the exception of heterotrophic respiration (Rh), for which modelling efficiency (EF) values were negative, the model outputs were in agreement with observations (e.g., EF ranging from ~0.2 for total soil respiration to ~0.7 for soil temperature). These results support the effectiveness of PaSim to simulate C cycle components in Mediterranean grasslands. The study also highlights the need of further model development to provide better representation of the seasonal dynamics of Mediterranean annual species‐rich grasslands and associated peculiar Rh features, for which the modelling is only implicitly being undertaken by the current PaSim release.

Confronting an individual-based simulation model with empirical community patterns of grasslands

“…Accounting for additional factors and their integration in grassland models, however, needs careful consideration in terms of potential changes in model behavior [48], especially when moving to other ecoregions (e.g. Mediterranean grasslands characterized by shifted growing-seasons to autumn-spring, summer drought and variable precipitation [49]). While the GRASSMIND model simulates the biogeochemical growth of individual plants interacting with each other in their neighborhood, other comparable grassland models simplify specific processes in favor of applicability [15].…”

“…Accounting for additional factors and their integration in grassland models, however, needs careful consideration in terms of potential changes in model behavior [ 48 ], especially when moving to other ecoregions (e.g. Mediterranean grasslands characterized by shifted growing-seasons to autumn-spring, summer drought and variable precipitation [ 49 ]).…”

The Use of Thermal Time to Describe and Predict the Growth and Nutritive Value of Lolium perenne L. and Bromus valdivianus Phil

“…However, the maximum grass growth was estimated at 30 AGDD before what was observed in the field. Pulina et al [35] suggested that these differences could be attributed to the sensitivity of the models to extreme values during data collection.…”

Effects of Grazing Management on Spatio-Temporal Heterogeneity of Soil Carbon and Greenhouse Gas Emissions of Grasslands and Rangelands: Monitoring, Modelling and Upscaling

“…Developing grazing ecosystem models can effectively support efforts to improve productivity and enhancing ecosystem services while tackling climate change impacts. Many process-based models have been developed for grazing lands, such as the Pasture Simulation model (PaSim) [67], NGAUGE [68], Denitrification Decomposition (DNDC) [26,69], DayCent [28], Roth-C [70]. Here, we do not to perform a full review of various agroecosystem models but illustrate some common approaches of simulating grazing lands through several typical BGC-AES models.…”