A heteroskedastic model of park grass spring hay yields in response to weather suggests continuing yield decline with climate change in future decades

A - Papers appearing in refereed journals

Addy, J. W. G., Ellis, R. H., MacLaren, C., Macdonald, A. J., Semenov, M. A. and Mead, A. 2022. A heteroskedastic model of park grass spring hay yields in response to weather suggests continuing yield decline with climate change in future decades. Journal of the Royal Society Interface. 19, p. 20220361. https://doi.org/10.1098/rsif.2022.0361

AuthorsAddy, J. W. G., Ellis, R. H., MacLaren, C., Macdonald, A. J., Semenov, M. A. and Mead, A.
Abstract

UK grasslands perform important environmental and economic functions, but their future productivity under climate change is uncertain. Spring hay yields from 1902 to 2016 at one site (the Park Grass Long Term Experiment) in southern England under four different fertiliser regimes were modelled in response to weather (seasonal temperature and rainfall). The modelling approach applied comprised: (1) a Bayesian model comparison to model parametrically the heteroskedasticity in a Gamma likelihood function; (2) a Bayesian varying intercept multiple regression model with an autoregressive lag one process (to incorporate the effect of productivity in the previous year) of the response of hay yield to weather from 1902 to 2016. The model confirmed that warmer and drier years, specifically, autumn, winter and spring, in the 20th and 21st centuries reduced yield. The model was applied to forecast future spring hay yields at Park Grass under different climate change scenarios (HadGEM2 and GISS RCP 4.5 and 8.5). This application indicated that yields are forecast to decline further between 2020 and 2080, by as much as 48-50%. These projections are specific to Park Grass, but implied a severe reduction in grassland productivity in southern England with climate change during the 21st century.

KeywordsClimate change; Fertilizer; Grassland; Hay; Long-term experiment; Rainfall; Yield; Temperature; UK; Fertiliser; Ecology; Applied statistics
Year of Publication2022
JournalJournal of the Royal Society Interface
Journal citation19, p. 20220361
Digital Object Identifier (DOI)https://doi.org/10.1098/rsif.2022.0361
Open accessPublished as green open access
FunderLawes Agricultural Trust
Funder project or codeThe Rothamsted Long Term Experiments [2017-2022]
Output statusPublished
Publication dates
Online24 Aug 2022
Publication process dates
Accepted26 Jul 2022
PublisherRoyal Society Publishing
ISSN1742-5689

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