Assessing cross-sectoral climate change impacts, vulnerability and adaptation: an introduction to the CLIMSAVE project

Harrison, Paula A.; Holman, Ian P.; Berry, Pam

doi:10.1007/s10584-015-1324-3

Cited by 61 publications

(53 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Involving stakeholders in such future models and scenario development exercises (e.g. as undertaken in the CLIMSAVE project [62]) could significantly advance strategies for adaptive Lyme disease management under environmental change.…”

Section: Discussionmentioning

confidence: 99%

Modelling the seasonality of Lyme disease risk and the potential impacts of a warming climate within the heterogeneous landscapes of Scotland

Gilbert

Harrison

et al. 2016

J. R. Soc. Interface.

View full text Add to dashboard Cite

Lyme disease is the most prevalent vector-borne disease in the temperate Northern Hemisphere. The abundance of infected nymphal ticks is commonly used as a Lyme disease risk indicator. Temperature can influence the dynamics of disease by shaping the activity and development of ticks and, hence, altering the contact pattern and pathogen transmission between ticks and their host animals. A mechanistic, agent-based model was developed to study the temperature-driven seasonality of Ixodes ricinus ticks and transmission of Borrelia burgdorferi sensu lato across mainland Scotland. Based on 12-year averaged temperature surfaces, our model predicted that Lyme disease risk currently peaks in autumn, approximately six weeks after the temperature peak. The risk was predicted to decrease with increasing altitude. Increases in temperature were predicted to prolong the duration of the tick questing season and expand the risk area to higher altitudinal and latitudinal regions. These predicted impacts on tick population ecology may be expected to lead to greater tick-host contacts under climate warming and, hence, greater risks of pathogen transmission. The model is useful in improving understanding of the spatial determinants and system mechanisms of Lyme disease pathogen transmission and its sensitivity to temperature changes.

show abstract

Section: Discussionmentioning

confidence: 99%

Modelling the seasonality of Lyme disease risk and the potential impacts of a warming climate within the heterogeneous landscapes of Scotland

Gilbert

Harrison

et al. 2016

J. R. Soc. Interface.

View full text Add to dashboard Cite

show abstract

“…Harrison et al 2016). Such decision-centred, cross-sectoral examples of how to successfully adapt are considered salient for adaptation decision-making Harrison et al 2015;Jäger et al 2015;Skourtos et al 2015). This perceived lack may explain why these decision-makers do not find information about, for example, the differences between 2 or 3 degree temperature changes to be useful for their adaptation decision-making.…”

Section: Discussionmentioning

confidence: 99%

To what extent are land resource managers preparing for high-end climate change in Scotland?

Dunn

Rounsevell

Carlsen³

et al. 2017

Climatic Change

View full text Add to dashboard Cite

We explore the individual and institutional conditions and the climate information used to underpin decision-making for adaptation to high-end climate change (HECC) scenarios in a land resource management context. HECC refers to extreme projections with global annual temperature increases of over 4°C. We analyse whether HECC scenarios are used in the adaptation decision-making of stakeholders who will tackle the potential problem. We also explore whether the adaptation actions being considered are pertinent only to future climate change or whether other drivers and information types are used in decision-making (including Climatic Change (2017) Adaptation Scotland/SNIFFER, Edinburgh, Scotland non-climate drivers). We also address the role of knowledge uncertainty in adaptation decision-making. Decision-makers perceive HECC as having a low probability of occurrence and so they do not directly account for HECC within existing actions to address climate change. Such actions focus on incremental rather than transformative solutions in which non-climate drivers are at least as important, and in many cases more important, than climate change alone. This reflects the need to accommodate multiple concerns and low risk options (i.e. incremental change). Uncertainty in climate change information is not a significant barrier to decision-making and stakeholders indicated little need for more climate information in support of adaptation decision-making. There is, however, an identified need for more information about the implications of particular sectoral and cross-sectoral impacts under HECC scenarios. The outcomes of this study provide evidence to assist in contextualising climate change information by creating usable, cross-sectoral, decision-centred information.

show abstract

“…The analysis uses the CLIMSAVE Integrated Assessment Platform (IAP 12,13 ), which links models of agriculture, forestry, urban growth, land use, water resources, flooding and biodiversity. The IAP is a spatiallyexplicit modelling platform that operates on a 10 x 10 minute grid for the countries of the European Union plus Norway and Switzerland.…”

Section: States: "Little Information Is Available On Integrated and Cmentioning

confidence: 99%

Climate change impact modelling needs to include cross-sectoral interactions

et al. 2016

View full text Add to dashboard Cite

Climate change impact assessments often apply models of individual sectors such as agriculture, forestry and water use without considering interactions between these sectors. This is likely to lead to misrepresentation of impacts, and consequently to poor decisions about climate adaptation. However, no published research assesses the differences between impacts simulated by single sector and integrated models. Here we compare 14 indicators derived from a set of impact models run within single sector and integrated frameworks across a range of climate and socio-economic scenarios in Europe. We show that single sector studies misrepresent the spatial pattern, direction and magnitude of most impacts because they omit the complex interdependencies within human and environmental systems. The discrepancies are particularly pronounced for indicators such as food production and water exploitation which are highly influenced by other sectors through changes in demand, land suitability and resource competition. Furthermore, the discrepancies are greater under different socio-economic scenarios than different climate scenarios, and at the sub-regional rather than Europe-wide scale.

show abstract

Assessing cross-sectoral climate change impacts, vulnerability and adaptation: an introduction to the CLIMSAVE project

Cited by 61 publications

References 27 publications

Modelling the seasonality of Lyme disease risk and the potential impacts of a warming climate within the heterogeneous landscapes of Scotland

Modelling the seasonality of Lyme disease risk and the potential impacts of a warming climate within the heterogeneous landscapes of Scotland

To what extent are land resource managers preparing for high-end climate change in Scotland?

Climate change impact modelling needs to include cross-sectoral interactions

Contact Info

Product

Resources

About