Identifying causes of low persistence of perennial ryegrass (Lolium perenne) dairy pasture using the Basic Grassland model (BASGRA)
Autor: | Simon Woodward, Pierre C. Beukes, Marcel van Oijen, Wendy M. Griffiths, David F. Chapman |
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Rok vydání: | 2020 |
Předmět: |
geography
geography.geographical_feature_category Perennial plant biology Water stress food and beverages Management Monitoring Policy and Law biology.organism_classification Pasture Lolium perenne Grassland Persistence (computer science) Agriculture and Soil Science Agronomy Grazing Environmental science Agronomy and Crop Science Bayesian calibration |
Zdroj: | Grass and Forage Science. 75:45-63 |
ISSN: | 1365-2494 0142-5242 |
DOI: | 10.1111/gfs.12464 |
Popis: | Recent years have seen a decline in herbage production and tiller populations in New Zealand's perennial ryegrass (Lolium perenne) dairy pastures. One hypothesis is that modern genotypes are less suited to the warmer, drier weather experienced under changing climate patterns. In this study, a combination of long‐term trial data (2011–2017) and a process‐based pasture model (BASGRA) was used to explore the causes and possible mitigation of the observed production and population loss at three sites (dryland sites in Northland and Waikato and an irrigated site in Canterbury). Bayesian calibration was used to identify the model parameter sets that were consistent with the trial data and to identify differences in plant morphology and responses between sites. The model successfully simulated the observed differences in tiller numbers between the dryland sites, where populations and production declined rapidly after the second year and the irrigated site where populations and production were maintained. Analysis of the model calibrations along with preliminary scenario simulations suggests that increased tiller mortality associated with drought was the main cause of persistence failure at the dryland sites and that decreasing grazing pressure or breeding for tolerance to higher temperatures may not be successful in preventing this. |
Databáze: | OpenAIRE |
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