adaptation in land-based sectors

Transcription

1 Behavioural models of climate change adaptation in land-based sectors Adaptation Futures conference Rotterdam, 10 May 2016 Calum Brown Peter Alexander, Sascha Holzhauer, Mark Rounsevell 1

2 The land & climate systems Human land use strongly sensitive to climate change, while also subject to demographic & dietary pressure 98% of land area where main food crops can be grown is subject to human activity adaptation essential but implies trade-offs Land use also a major driver of climate change (and possible contributor to mitigation): Agriculture accounts for ~ 1/3 rd of total anthropogenic greenhouse gas emissions, while managed forests may have absorbed up to 20% of those emissions in recent decades Photo: NASA Associated loss of biological diversity, half world s animal species, compromising ability of natural systems to adapt 2

3 Adaptation in the land system Process of adaptation also highly complex depends fundamentally on willingness and ability of people & societies to adapt Known that this in turn depends upon, e.g.: Education levels Social cohesion & equality Political rights & structures Personal values & knowledge Belief in climate change and ability to adapt effectively (Below et al. 2012; Naess 2013; Nay et al. 2014; Feola et al. 2015; Vulturius et al. in rev.) All of these factors are dynamic, including at macro-scale (e.g. institutional, governmental); interact with changing social context (Nilsson et al. 2004; Strauss 2012; Hastrup 2013; Brown et al. 2016) Photo: NASA -> Models that assume static or simple economic behaviour at individual and collective levels (i.e. through calibration to historical datasets) may produce misleading results 3

4 Behavioural modelling of land use change Behavioural modelling large and growing area of land system modelling Includes approaches such as agent-based modelling, multi-agent systems modelling, social simulation models - generally referred to as bottom-up or process-based models Systems treated as collections of individual entities rather than as entities in their own right Also: Autonomy (agency) Interactions with other agents Interactions with environment (Imperfect understanding of world) (proactive goal-directed decision-making) Photo: NASA 4

5 Behavioural modelling of land use change Accounting for range of relevant behaviours is a difficult task, especially at large scales and across land-based sectors Behavioural models difficult to develop, calibrate, validate and interpret Therefore (probably) need diversity of approaches, but with clear foundations and overall objectives Literature suggests some important requirements: Forms of behaviour Non- or supra-economic Diffusion, social networks Learning & anticipation Institutional behaviour Behavioural change Geographical extent Theoretical understanding Focused small-scale case studies Meaningful units (e.g. watershed) Cross-sectoral Continental-global scale for land system dynamics Model relevance Appropriate design & calibration Validation Photo: NASA Uncertainty assessment Transparency & availability 5

6 Behavioural modelling of land use change Accounting for range of relevant behaviours is a difficult task, especially at large scales and across land-based sectors Behavioural models difficult to develop, calibrate, validate and interpret Therefore (probably) need diversity of approaches, but with clear foundations and overall objectives Literature suggests some important requirements: Forms of behaviour Non- or supra-economic Diffusion, social networks Learning & anticipation Institutional behaviour Behavioural change Geographical extent Theoretical understanding Focused small-scale case studies Meaningful units (e.g. watershed) Cross-sectoral Continental-global scale for land system dynamics Model relevance Appropriate design & calibration Validation Photo: NASA Uncertainty assessment Transparency & availability What is the state-of-the-art in current modelling practice? 6

7 What is the state-of-the-art in current modelling practice? Aim: investigate the extent to which existing models of climate change adaptation in land use address relevant behaviours, under range of climate impacts, across sectors and scales ISI Web of Knowledge search (September 2015), keywords: land use, land cover, land based, agriculture, agricultural, forest, restore, restoration, conservation, rewild, ecosystem, climate change, behaviour, behavior, behavioural, behavioral, agent, model, modelling, modeling 1,393 papers of which 38 found to describe relevant models Record details about modelling undertaken, behavioural processes and actors included, forms of adaptation (or mitigation) permitted, modelled impacts of climate change, and methods of validation and uncertainty estimation 7

8 0 No. models 25 10/05/2016 Economic, Diffusion, Learning, Institutional Behavioural change, individual social networks anticipation behaviour 2 nd order learning Behavioural complexity AGRICULTURE FORESTRY CONSERVATION URBAN COASTAL 8

9 0 No. models 25 10/05/2016 Economic, Diffusion, Learning, Institutional Behavioural change, individual social networks anticipation behaviour 2 nd order learning Behavioural complexity AGRICULTURE FORESTRY CONSERVATION URBAN COASTAL 9

10 0 No. models 25 10/05/2016 Economic, Diffusion, Learning, Institutional Behavioural change, individual social networks anticipation behaviour 2 nd order learning Behavioural complexity AGRICULTURE FORESTRY CONSERVATION URBAN COASTAL 10

11 0 No. models 25 10/05/2016 Economic, Diffusion, Learning, Institutional Behavioural change, individual social networks anticipation behaviour 2 nd order learning Behavioural complexity AGRICULTURE FORESTRY CONSERVATION URBAN COASTAL 11

12 0 No. models 25 10/05/2016 Economic, Diffusion, Learning, Institutional Behavioural change, individual social networks anticipation behaviour 2 nd order learning Behavioural complexity AGRICULTURE FORESTRY CONSERVATION URBAN COASTAL 12

13 0 No. models 25 10/05/2016 Economic, Diffusion, Learning, Institutional Behavioural change, individual social networks anticipation behaviour 2 nd order learning Behavioural complexity AGRICULTURE FORESTRY CONSERVATION URBAN COASTAL 13

14 Overall findings: Agriculture far more often modelled than forestry, conservation, water management or subsistence Crop selection most commonly modelled decision Agricultural models also behaviourally richer Forestry change often a simple, direct consequence of agricultural change Active climate change not always simulated, and only a narrow range of impacts included Water resource availability by far the most commonly modelled climate change impact (occasionally yields) Both adaptation and mitigation generally modelled as responses to economic drivers rather than climate change Maladaptation never allowed for 14

15 Behavioural findings: Majority of models base behaviour on economic responses only Diffusion of practices frequently modelled, but diffusion of attitudes very rare Institutions often seen as too complex and included via scenarios at best Learning and anticipation not usually included in great detail Dynamic behaviours that change with context almost completely absent Water management and subsistence models place more emphasis on institutional and social contexts respectively 15

16 Geographical extent Good coverage of theoretical effects and small-scale case studies Clear group of models focus on large but sub-national scales often following political boundaries No models of adaptation behaviour above national scale 16

17 Model relevance Model transparency and availability varies widely, no standard practice Some very rigorous approaches to validation & uncertainty but often not mentioned or not fully robust Few justifications given for chosen approach, or consideration of implications for findings 17

18 Conclusions priorities for behavioural modelling Behavioural modelling of climate change adaptation not generally perceived as coherent field Many discrete model applications lacking overall synergies More behavioural richness required, particularly in non-agricultural models Cross-sectoral models needed for projecting competition and trade-offs Dynamic, rather than static, behaviours Up-scaling to assess behavioural effects across land systems Representation of a wider range of active climate change impacts Identification and adoption of good practice in validation, uncertainty analysis, interpretation and availability 18

19 Questions? 19