Literature DB >> 36000226

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

John W G Addy1, Richard H Ellis2, Chloe MacLaren1, Andy J Macdonald1, Mikhail A Semenov1, Andrew Mead1.   

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 fertilizer 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 twentieth and twenty-first 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 twenty-first century.

Entities:  

Keywords:  applied statistics; climate change; ecology; fertilizer; grassland; yield

Mesh:

Year:  2022        PMID: 36000226      PMCID: PMC9399698          DOI: 10.1098/rsif.2022.0361

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.293


  14 in total

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4.  Modeling bias and variation in the stochastic processes of small RNA sequencing.

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Journal:  Sci Total Environ       Date:  2018-04-11       Impact factor: 7.963

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Authors:  Qingzhu Gao; Wenquan Zhu; Mark W Schwartz; Hasbagan Ganjurjav; Yunfan Wan; Xiaobo Qin; Xin Ma; Matthew A Williamson; Yue Li
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Review 9.  The influence of rising tropospheric carbon dioxide and ozone on plant productivity.

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10.  Stomatal conductance limited the CO2 response of grassland in the last century.

Authors:  Juan C Baca Cabrera; Regina T Hirl; Rudi Schäufele; Andy Macdonald; Hans Schnyder
Journal:  BMC Biol       Date:  2021-03-24       Impact factor: 7.431

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