Adaptation to increasing severity of phoma stem canker on winter oilseed rape in the UK under climate change
Year: 2010
Type: article
Abstract: SUMMARY Various adaptation strategies are available that will minimize or negate predicted climate change-related increases in yield loss from phoma stem canker in UK winter oilseed rape (OSR) production. A number of forecasts for OSR yield, national production and subsequent economic values are presented, providing estimates of impacts on both yield and value for different levels of adaptation. Under future climate change scenarios, there will be increasing pressure to maintain yields at current levels. Losses can be minimized in the short term (up to the 2020s) with a ‘low’-adaptation strategy, which essentially requires some farmer-led changes towards best management practices. However, the predicted impacts of climate change can be negated and, in most cases, improved upon, with ‘high’-adaptation strategies. This requires increased funding from both the public and private sectors and more directed efforts at adaptation from the producer. Most literature on adaptation to climate change has had a conceptual focus with little quantification of impacts. It is argued that quantifying the impacts of adaptation is essential to provide clearer information to guide policy and industry approaches to future climate change risk.
Authors: A. P. BARNES, A. WREFORD, M. H. BUTTERWORTH, M. A. SEMENOV, D. MORAN, N. EVANS, B. D. L. FITT
Institutions: Scottish Agricultural Science Agency, Rothamsted Research
Language: English
Subfield: Agronomy and Crop Science
Domain: Life Sciences
SDGs: Zero hunger, Climate action
Open Access status: green
Awards: Understanding interactions between climate change, arable crop growth and disease epidemics, G1795775161, Understanding resistance to decrease risk of severe phoma stem canker on oilseed rape, Targeting symptomless pathogen growth to control fungal plant diseases, Application of non-linear mathematics and stochastic modelling to complex biological systems
OpenAlex ID: W2044512432
