Farm-level Autonomous Adaptation of European Agricultural Supply to Climate Change

Leclère, David; Jayet, Pierre-Alain; Noblet‐Ducoudré, Nathalie de

doi:10.1016/j.ecolecon.2012.11.010

Cited by 85 publications

(38 citation statements)

References 37 publications

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“…Results presented in Figure 2 also indicate that a considerable part of the uncertainty in projecting future crop yield may originate from the fact that we do not know much about the extent and type of adaptations that will take place at farm level in response to a changing climate (see, e.g. Leclère et al, 2013). The projections of technology trends that have been made for 2050 and beyond (e.g.…”

Section: Jun−augmentioning

confidence: 92%

Projections of climate change impacts on crop production: A global and a Nordic perspective

Rötter

Höhn

Fronzek

2012

Acta Agriculturae Scandinavica, Section A – Animal Science

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Global climate is changing and food production is very sensitive to weather and climate variations. Global assessments of climate change impacts on food production have been made since the early 1990s, initially with little attention to the uncertainties involved. Although there has been abundant analysis of uncertainties in future greenhouse gas emissions and their impacts on the climate system, uncertainties related to the way climate change projections are scaled down as appropriate for different analyses and in modelling crop responses to climate change, have been neglected. This review paper mainly addresses uncertainties in crop impact modelling and possibilities to reduce them. We specifically aim to (i) show ranges of projected climate change-induced impacts on crop yields, (ii) give recommendations on use of emission scenarios, climate models, regionalization and ensemble crop model simulations for different purposes and (iii) discuss improvements and a few 'known unknowns' affecting crop impact projections.

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Section: Jun−augmentioning

confidence: 92%

Projections of climate change impacts on crop production: A global and a Nordic perspective

Rötter

Höhn

Fronzek

2012

Acta Agriculturae Scandinavica, Section A – Animal Science

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“…Despite these benefits, grasslands have declined in Europe, with an estimated loss of seven million hectares between 1967 and 2007 (Huyghe et al, 2014). Recent predictions suggest that this decline may continue in a climate change future (Leclère et al, 2013). In this context, a better understanding is required of the impacts of climate change on European grassland systems, the efficacy of adaptation strategies to increase their resilience and productivity, and the pathways available to maintain and enhance the essential ecosystem services they provide (Scollan et al, 2010;Smith et al, 2013).…”

Section: Introductionmentioning

confidence: 98%

Key challenges and priorities for modelling European grasslands under climate change

Kipling

Virkajärvi

Breitsameter

et al. 2016

Science of The Total Environment

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Grassland-based ruminant production systems are integral to sustainable food production in Europe, converting plant materials indigestible to humans into nutritious food, while providing a range of environmental and cultural benefits. Climate change poses significant challenges for such systems, their productivity and the wider benefits they supply. In this context, grassland models have an important role in predicting and understanding the impacts of climate change on grassland systems, and assessing the efficacy of potential adaptation and mitigation strategies. In order to identify the key challenges for European grassland modelling under climate change, modellers and researchers from across Europe were consulted via workshop and questionnaire. Participants identified fifteen challenges and considered the current state of modelling and priorities for future research in relation to each. A review of literature was undertaken to corroborate and enrich the information provided during the horizon scanning activities. Challenges were in four categories relating to: 1) the direct and indirect effects of climate change on the sward 2) climate change effects on grassland systems outputs 3) mediation of climate change impacts by site, system and management and 4) cross-cutting methodological issues. While research priorities differed between challenges, an underlying theme was the need for accessible, shared inventories of models, approaches and data, as a resource for stakeholders and to stimulate new research. Developing grassland models to effectively support efforts to tackle climate change impacts, while increasing productivity and enhancing ecosystem services, will require engagement with stakeholders and policy-makers, as well as modellers and experimental researchers across many disciplines. The challenges and priorities identified are intended to be a resource 1) for grassland modellers and experimental researchers, to stimulate the development of new research directions and collaborative opportunities, and 2) for policy-makers involved in shaping the research agenda for European grassland modelling under climate change.

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“…Studies to simulate regional or time series crop yields, as with crop growth models, have often held planting dates static over space and/or time to focus on model sensitivity to other inputs (Leclère et al. , Bassu et al. , Mast et al.…”

Section: Introductionmentioning

confidence: 99%

Cause and Consequence in Maize Planting Dates in Germany

Parker

Shonkwiler

Aurbacher

2016

J Agronomy Crop Science

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An important part of agricultural adaptation is the timing of crop sowing dates, affecting yields and the level of risk incurred during a particular season. Cold stress is especially relevant in maize, Zea mays L., so that the timing of planting in the spring is a tactical response to short‐term weather, but is also subject to strategic planning with regard to longer‐term climate. Both factors compare the potential implications of cold stress to the additional yield obtainable through earlier planting. New cultivars suited to growing conditions in Europe and generally increasing spring temperatures have enabled earlier planting, but it is still dependent on short‐term weather during the planting period. In the context of field‐level decision‐making, a panel regression is used to estimate the relationship between weekly local temperature and precipitation and planting dates at specific sites throughout Germany. Next, localised weather data and planting behaviour are linked to yields at the district (Landkreis) level to show the effects of planting date on yield. Based on these relationships optimal planting dates are explored with some associated costs and benefits. Results show a trend towards earlier planting that follows observed increasing spring temperatures and the availability of more cold‐tolerant cultivars but this advance is buffered by the increasing severity of minimum temperatures during a critical period. Earlier planting potentially increases yield but this is offset by additional management costs and risk. A robust and simple depiction of farmer behaviour in climatic, technological and economic context can help to understand trends in crop management and productivity that effect agricultural landscapes.

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Farm-level Autonomous Adaptation of European Agricultural Supply to Climate Change

Cited by 85 publications

References 37 publications

Projections of climate change impacts on crop production: A global and a Nordic perspective

Projections of climate change impacts on crop production: A global and a Nordic perspective

Key challenges and priorities for modelling European grasslands under climate change

Cause and Consequence in Maize Planting Dates in Germany

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